Datasets

The following pages describe over 300 datasets that are available for this course. All data, except for Appleby's Red Deer data set, are coded in the UCINET DL format. The Red Deer data are presented simply as a text file that contains a report of a sequence of detailed observations. Multirelational data are stored, when possible, in a single multirelational data file. Each relation within a multirelational set is labelled and information about the form of the data is described for each individual matrix.

Top of the List


ADAMIC,GLANCE--POLITICAL BLOGS

DATASET BLOGS

DESCRIPTION One 1490×1490 non-symmetric binary matrix stored as an edgelist.

BACKGROUND The data were compiled by Lada Adamic and Natalie Glance. Links between blogs were automatically extracted from a crawl of the front page of the blog. In addition the authors drew on various sources (blog directories, and incoming and outgoing links and posts around the time of the 2004 presidential election) and classified the first 758 blogs as left-leaning and the remaining 732 as right-leaning.

REFERENCE

  • Lada A. Adamic and Natalie Glance, "The political blogosphere and the 2004 US election", Proceedings of the WWW-2005 Workshop on the Weblogging Ecosystem (2005). Available at:
    http://www2.scedu.unibo.it/roversi/SocioNet/AdamicGlanceBlogWWW.pdf

List of Datasets


APPLEBY--RED DEER DOMINANCE

FILES REDDEER REDDEER_CODES

DESCRIPTION

REDDEER is not a DL file. Instead it is simply a time-ordered list containing 2008 observations of dominance encounters between pairs of red deer stags. The data on encounters were collected from January to March in 1978.

They were obtained during a series of watches on 20 focal individuals, 2 of each age from 2 to 11 years old. Thus, most of the data involve the focal individuals.

REDDEER_CODES is a sheet that explains all the codes used in REDDEER.

REFERENCES

  • M. C. Appleby, "Social rank and food access in red deer stags," Behaviour, 1980, 74: 294-309. describes the research.
  • M. C. Appleby. 1983. "Competition in a red deer stag social group: rank, age and relatedness of opponents." Animal Behaviour 31: 913-918.
  • List of datasets


    BASHAW,BLOOMSMITH,MAPLE,BERCOVITCH--GIRAFFE AFFILIATION

    DATASET GIRAFFE

    DESCRIPTION Three 6×6 matrices.

    AFFIL non-symmetric, valued.
    PROXIMITY non-symmetric, valued.
    NEIGHBOR non-symmetric, valued.

    BACKGROUND The authors studied a herd of six female captive giraffe (Giraffa camelopardalis) for two years. They were concerned with the question of whether giraffe associated randomly or patterned their behavior and proximity in a manner indicative of social relationships. Affiliative interaction, proximity, and nearest neighbors for female giraffe living in a large outdoor enclosure were analyzed, and all three measures were nonrandomly distributed, indicating female giraffe had social preferences. Furthermore, preferences were consistent across measures and time, suggesting that adult female giraffe maintain relationships.

    REFERENCE Brashaw, M. J., M. A. Bloomsmith, T. L. Maple and F. B. Bercovitch. 2007. "The Structure of Social Relationships Among Captive Female Giraffe (Giraffa camelopardalis)." Journal of Comparative Psychology 121:46-53.

    List of datasets


    BERNARD,KILLWORTH,SAILER--FRATERNITY

    DATASET BKFRAT

    DESCRIPTION Two 58×58 matrices:

    BKFRAB symmetric, valued.
    BKFRAC non-symmetric, valued (rankings).

    BACKGROUND Bernard & Killworth, later with the help of Sailer, collected five sets of data on human interactions in bounded groups and on the actors' ability to recall those interactions. In each study they obtained measures of social interaction among all actors, and ranking data based on the subjects' memory of those interactions. The names of all cognitive (recall) matrices end in C, those of the behavioral measures in B.

    These data concern interactions among students living in a fraternity at a West Virginia college. All subjects had been residents in the fraternity from three months to three years. BKFRAB records the number of times a pair of subjects were seen in conversation by an "unobtrusive" observer (who walked through the public areas of the building every fifteen minutes, 21 hours a day, for five days). BKFRAC contains rankings made by the subjects of how frequently they interacted with other subjects in the observation week.

    REFERENCES

    • Bernard H. R., Killworth P. and Sailer L. (1980). Informant accuracy in social network data IV. Social Networks, 2, 191-218.
    • Bernard H. R., Killworth P. and Sailer L. (1982). Informant accuracy in social network data V. Social Science Research, 11, 30-66.
    • Romney A. K. and Weller S. (1984). Predicting informant accuracy from patterns of recall among individuals. Social Networks, 6, 59-78.

    List of datasets


    BERNARD,KILLWORTH,SAILER--OFFICE

    DATASET BKOFF

    DESCRIPTION Two 40×40 matrices.

    BKOFFB symmetric, valued.
    BKOFFC non-symmetric, valued (rankings)

    BACKGROUND Bernard & Killworth, later with the help of Sailer, collected five sets of data on human interactions in bounded groups and on the actors' ability to recall those interactions. In each study they obtained measures of social interaction among all actors, and ranking data based on the subjects' memory of those interactions. The names of all cognitive (recall) matrices end in C, those of the behavioral measures in B.

    These data concern interactions in a small business office, again recorded by an "unobtrusive" observer. Observations were made as the observer patrolled a fixed route through the office every fifteen minutes during two four-day periods. BKOFFB contains the observed frequency of interactions; BKOFFC contains rankings of interaction frequency as recalled by the employees over the two-week period.

    REFERENCES See citations to the previous datasets.

    List of datasets


    BERNARD,KILLWORTH,SAILER--TECHNICAL

    DATASET BKTEC

    DESCRIPTION Two 34×34 matrices.

    BKTECB symmetric, valued
    BKTECC non-symmetric, valued (rankings).

    BACKGROUND Bernard & Killworth, later with the help of Sailer, collected five sets of data on human interactions in bounded groups and on the actors' ability to recall those interactions. In each study they obtained measures of social interaction among all actors, and ranking data based on the subjects' memory of those interactions. The names of all cognitive (recall) matrices end in C, those of the behavioral measures in B.

    These data concern interactions in a technical research group at a West Virginia university. BKTECB contains a frequency record of interactions, made by an observer every half-hour during one five-day work week. BKTECC contains the personal rankings of the remembered frequency of interactions in the same period.

    REFERENCES See citations to the previous datasets.

    List of datasets


    BOTT--PRESCHOOL

    DATASETS BOTT BOTT_ATTRIBUTE

    DESCRIPTION

    BOTT: Five 11×11 matrices:

    TALK non-symmetric, valued.
    INTERFERE non-symmetric, valued.
    WATCH non-symmetric, valued.
    IMITATE non-symmetric, valued.
    COOPERATE non-symmetric, valued.

    BOTT_ATTRIBUTE: One 11×1 valued vector of ages

    BACKGROUND The data were collected in 1926 in a preschool in Toronto. Observations were made on each child in turn who was defined as a "focal" individual. Instances in which the focal child (1) talked to another, (2) interfered with another, (3) watched another, (4) imitated another or (5) cooperated with another were tabulated along with the name of the other to whom the social behavior was directed. The result was tabulated in five matrices. Female children are identified with an astrisk on their row and column label.

    REFERENCE

    • Bott, H. "Observations of play activities in a nursery school," Genetic Psychology Monographs, 1928, 4: 44-88.

    List of datasets


    CLUTON-BROCK,GREENWOOD,POWELL--HIGHLAND PONY DOMINANCE

    DATASET PONY

    DESCRIPTION One 17×17 frequency matrix.

    BACKGROUND Cell entries are the number of occasions in which the row pony threatened the column pony. The main diagonal is uniformly set to zero. The order was imposed using the Schein and Frohman algorithm.

    REFERENCES

  • T.H.Cluton-Brock, J.P.Greenwood and R.P.Powell, 1976, "Ranks and Relationships in Highland Ponies and Highland Cows," Zeitschrify Tierpsychologie, 41, 202-216.
  • M.W.Schein and M.W.Frohman, 1955, "Social Dominance Relationships in a Herd of Dairy-Cattle," British Journal of Animal Behaviour, 3, 45-55 (1955).
  • List of datasets


    COLE--ANT DOMINANCE

    DATASETS ANTS_1 ANTS_2

    DESCRIPTION Two communities of ants. One is a 16×16 non-symmetric matrix of frequencies and the other is a 13×13 non-symmetric matrix of frequencies.

    ANTS_1 non-symmetric, valued dominance
    ANTS_2 non-symmetric, valued dominance

    BACKGROUND These are observations of ritual dominance activities in two ant communities. The first is a collection of 16 female Leptothorax allardycei ants over 18.2 hours in a queenright colony. They were observed over 18.2 hours. The second is a collection of 13 female Leptothorax allardycei ants in a queenless colony. They were observed over 14.8 hours.

    REFERENCE

  • B. J. Cole, 1981, "Dominance hierarchies in Leptothorax ants," Science, 212: 83-84.
  • List of datasets


    COLEMAN--FRIENDSHIPS AMONG HIGH SCHOOL BOYS

    DATASET HIGHSCHL

    DESCRIPTION Two 73×73 matrices:

    TIME1 non-symmetric, binary.
    TIME2 non-symmetric, binary.

    BACKGROUND In the fall of 1957. and the spring of 1958. boys in a small high school in Illinois were asked. "What fellows here in school do you go around with most often?" The data are from research reported by Coleman. The data report the direct choices of each of 73 boys at two times. HS1 was recorded in 1957 and HS2 in 1958.

    REFERENCE

    • Coleman, J. S. Introduction to Mathermatical Sociology. New York: Free Press, pp.450-451.

    List of datasets


    COLEMAN,KATZ,MENZEL--INNOVATION AMONG PHYSICIANS

    DATASETS CKM ATTRIBUTES

    DESCRIPTION

    CKM: Three 246×246 matrices:

    ADVICE non-symmetric, binary.
    DISCUSSION non-symmetric, binary.
    FRIEND non-symmetric, binary.

    ATTRIBUTES: One 246×13 valued matrix

    BACKGROUND This data set was prepared by Ron Burt. He dug out the 1966 data collected by Coleman, Katz and Menzel on medical innovation. They had collected data from physicians in four towns in Illinois, Peoria, Bloomington, Quincy and Galesburg.

    They were concerned with the impact of network ties on the physicians' adoprion of a new drug, tetracycline. Three sociometric matrices were generated. One was based on the replies to a question, "When you need information or advice about questions of therapy where do you usually turn?" A second stemmed from the question "And who are the three or four physicians with whom you most often find yourself discussing cases or therapy in the course of an ordinary week -- last week for instance?" And the third was simply "Would you tell me the first names of your three friends whom you see most often socially?"

    In addition, records of prescriptions were reviewed and a great many other questions were asked. In the ATTRIBUTES data I have included 13 items: city of practice, recorded date of tetracycline adoption date, years in practice, meetings attended, journal subscriptions, free time activities, discussions, club memberships, friends, time in the community, patient load, physical proximity to other physicians and medical specialty.

    The codes are:
    City: 1 Peoria, 2 Bloomington, 3 Quincy, 4 Galesburg

    Adoption Date:
    1 November, 1953
    2 December, 1953
    3 January, 1954
    4 February, 1954
    5 March, 1954
    6 April, 1954
    7 May, 1954
    8 June, 1954
    9 July, 1954
    ) 10 August, 1954
    11 September, 1954
    12 October, 1954
    13 November, 1954
    14 December, 1954
    15 December/January, 1954/1955
    16 January/February, 1955
    17 February, 1955
    18 no prescriptions found
    98 no prescription data obtained

    Year started in the profession
    1 1919 or before
    2 1920-1929
    3 1930-1934
    4 1935-1939
    5 1940-1944
    6 1945 or later
    9 no answer

    Have you attended any national, regional or state conventions of professional societies during the last 12 months? [if yes] Which ones?
    0 none
    1 only general meetings
    2 specialty meetings
    9 no answer

    Which medical journals do you receive regularly?
    1 two
    2 three
    3 four
    4 five
    5 six
    6 seven
    7 eight
    8 nine or more
    9 no answer

    With whom do you actually spend more of your free time -- doctors or non-doctors?
    1 non-doctors
    2 about evenly split between them
    3 doctors
    9 mssing; no answer, don't know

    When you are with other doctors socially, do you like to talk about medical matter?
    1 no
    2 yes
    3 don't care
    9 missing; no answer, don't know

    Do you belong to any club or hobby composed mostly of doctors?
    0 no
    1 yes
    9 no answer

    Would you tell me who are your three friends whom you see most often socially? What is [their] occupation?
    1 none are doctors
    2 one is a doctor
    3 two are doctors
    4 three are doctors
    9 no answer

    How long have you been practicing in this community?
    1 a year or less
    2 more than a year, up to two years
    3 more than two years, up to five years
    4 more than five years, up to ten years
    5 more than ten years, up to twenty years
    6 more than twenty years
    9 no answer

    About how many office visits would you say you have during the average week at this time of year?
    1 25 or less
    2 26-50
    3 51-75
    4 76-100
    5 101-150
    6 151 or more
    9 missing; no answer, don't know

    Are there other physicians in this building? [if yes] Other physicians in same office or with same waiting room?
    1 none in building
    2 some in building, but none share his office or waiting room
    3 some in building sharing his office or waiting room
    4 some in building perhaps sharing his office or waiting room
    9 no answer

    Do you specialize in any particular field of medicine? [if yes] What is it?
    1 GP, general practitioner
    2 internist
    3 pediatrician
    4 other specialty
    9 no answer

    REFERENCES

    • Burt, Ronald S. 1987. "Social Contagion and Innovation: Cohesion Versus Structural Equivalence," AJS 92: 1287-1335.
    • Burt, R., (1987). Social contagion and innovation: Cohesion versus structural equivalence. American Journal of Sociology, 1987. 92: p. 1287-1335.
    • Coleman, James, Elihu Katz and Herbert Menzel. 1957. "The Diffusion of an Innovation Among Physicians," Sociometry, 20:253-270.
    • Coleman, J.S., E. Katz, and H. Menzel, 1966. Medical Innovation: A Diffusion Study. New York: Bobbs Merrill.
    • Valente, T. W. (1995). Network Models of the Diffusion of Innovations. Cresskill, NJ: Hampton Press.
    • Van den Bulte, C. and G. L. Lilien. 2001. "Medical Innovation Revisited: Social Contagion versus Marketing Effort,"AJS 106: 1409-1435.

    List of datasets


    CONNER,SMOLKER,RICHARDS--DOLPHIN GROUPS

    DATASET DOLPHIN

    DESCRIPTION One 13×13 frequency matrix.

    BACKGROUND Thirteen male dolphins were observed as they swam in a shallow lagoon. Tabulations were made of who was swimming with whom. The table shows the observed frequencies.

    REFERENCE

    • R. C. Connor, R. A. Smolker and A. F. Richards, 1992, "Dolphin alliances and coalitions," in Coalitions and Alliances in Humans and Other Animals (Eds: A. H. Harcourt and F. B. M. deWaal). Oxford: Oxford University Press, 415-444.

    List of datasets


    DAVIS,GARDNER,GARDNER--SOUTHERN WOMEN

    DATASET DAVIS

    DESCRIPTION One 18×14 two mode binary matrix.

    BACKGROUND These data were collected by Davis et al. in the 1930s. They represent observed attendance at 14 small social events by 18 Southern women. The result is a person-by-event matrix: cell (i,j) is 1 if person i attended social event j, and 0 otherwise.

    REFERENCES

    • Breiger R. (1974). The duality of persons and groups. Social Forces, 53, 181-190.
    • Davis, A. et al. (1941). Deep South. Chicago: University of Chicago Press.

    List of datasets


    FREEMAN,FREEMAN,MICHAELSON--BEACH

    DATASET BEACH

    DESCRIPTION Two 43×43 matrices:

    BB symmetric, valued, observed interaction.
    BC symmetric, valued, judged closeness.

    BACKGROUND This was a study of windsurfers on a beach in southern California during the fall of 1986. The windsurfing community was fairly clearly divided into at least two sub-communities. Members of each community seemed, to some degree, to limit their interaction to fellow group members. Contacts between members of the two groups occurred, but these were less frequent. Observations of 43 individuals were made for 31 days. All interpersonal contacts among collections of these individuals were recorded. Then all 43 individuals were interviewed following the end of observation. Data on each individual's perception of social affiliations were collected.

    The perceptual data were generated by asking each subject to perform a sequence of card sorting tasks that assigned an index of the perceived closeness of every individual on the beach to each of the other individuals.

    REFERENCES

    • L. C. Freeman, S. C. Freeman and A. G. Michaelson "On Human Social Intelligence." Journal of Social and Biological Structures, 11, 1988, 415-425.
    • L. C. Freeman, S. C. Freeman and A. G. Michaelson "How Humans See Social Groups: A Test of the Sailer-Gaulin Models." Journal of Quantitative Anthropology, 1, 1989, 229-238.

    List of datasets


    FREEMAN,FREEMAN--EIES

    DATASETS EIES EIES_ATTRIBUTE

    DESCRIPTION

    EIES: Three 34×34 matrices:

    TIME_1 non-symmetric, valued.
    TIME_2 non-symmetric, valued.
    NUMBER_OF_MESSAGES non-symmetric, valued.

    EIES_ATTRIBUTE: One 34×2 valued matrix

    BACKGROUND These data arose from an early experiment on computer mediated communication. Fifty academics interested in social network research were allowed to contact each other via an Electronic Information Exchange System (EIES). The data collected consisted of all messages sent plus acquaintance relationships at two time periods (collected via a questionnaire).The data include the 32 actors who completed the study. In addition attribute data on primary discipline and number of citations was recorded.

    TIME_1 and TIME_2 give the reported acquaintance information at the beginning of the study and eight months later. These are coded as follows: 4 = close personal fiend, 3= friend, 2= person I've met, 1 = person I've heard of but not met, and 0 = person unknown to me (or no reply).

    NUMBER_OF MESSAGES is the total number of messages person i sent to j over the entire period of the study. The attribute data give the number of citations of the actors work in the social science citation index at the beginning of the study together with a discipline code: 1 = Sociology, 2 = Anthropology, 3 = Mathematics/Statistics, 4 = other. These data are used by Wasserman and Faust in their network analysis book.

    REFERENCES

    • Freeman, S. C. and L. C. Freeman (1979). The networkers network: A study of the impact of a new communications medium on sociometric structure. Social Science Research Reports No 46. Irvine CA, University of California.
    • Wasserman S. and K. Faust (1994). Social Network Analysis: Methods and Applications.Cambridge University Press, Cambridge.

    List of datasets


    FROELICH,THORINGTON,SAILER,GAULIN--HOWLER MONKEY GROUPS

    DATASETS HOWLER HOWLER_GROUPS

    DESCRIPTION One 17×17 symmetric matrix of frequencies. One 17×4 two mode binary matrix of monkeys by groups.

    HOWLER symmetric, valued
    HOWLER_GROUPS two mode binary monkeys by group assignments.

    BACKGROUND These data on 17 mantled howler monkeys, Alouatta palliata, were collected by Froehlich and Thorington (1981) and by Gaulin (Sailer & Gaulin, 1984). The monkeys were assigned to "troops" by Froehlich and Thorington, and Gaulin reported the results of ad libidum "co-observations" of collections of individuals. Monkeys 12 and 26 were juveniles, monkey 9 was an infant and the others were all adults. Monkeys 5, 9, 13, 16, 21, 25 and 27 were males; the others were females.

    REFERENCES

  • J. W. Froehlich and R. W. Thorington, Jr., 1981, "The genetic structure and socioecology of howler monkeys (Alouatta palliata) on Barro Colorado Island," in Ecology of Barro Colorado Island: Seasonal Rhythms and Long Term Changes in a Tropical Forest, ed. E. G. Leigh and A. S. Randi. Washington: Smithsonian Press.
  • L. D. Sailer and S. J. C. Gaulin, 1984, "Proximity, sociality and observation: the definition of social groups." American Anthropologist, 86:91-98.
  • List of datasets


    GALASKIEWICZ--CEO'S AND CLUBS

    DATASET GALAS

    DESCRIPTION One 26x15 affiliation matrix.

    BACKGROUND These data give the affiliation network of 26 CEO's of major corporations and banks and their spouses to 15 clubs, corporate and cultural boards.. Data were collected in the Minneapolis area. Membership was during the period 1978-1981.

    REFERENCE

    • Galaskiewicz J (1985). Social Organization of an Urban Grants Economy. New York. Academic Press.

    List of datasets


    GLEISER,DANON--COLLABORATION IN JAZZ

    DATASET JAZZ

    DESCRIPTION One 198×198 symmetric binary matrix.

    BACKGROUND The data here record a network of jazz bands. The data were obtained from The Red Hot Jazz Archive digital database. The data include 198 bands that performed between 1912 and 1940, with most of the bands performing in the 1920's. In this case each vertex corresponds to a band, and a link between two bands is established if they had at least one musician in common.

    REFERENCE

    • PABLO M. GLEISER and LEON DANON "Community structure in jazz." Advances in Complex Systems (ACS) 2003 Vol: 6 Issue: 4 (December 2003) Page: 565 - 573.

    List of datasets


    GRANT--KANGAROO PROXIMITIES AND RANKS

    DATASETS KANGAROO KANGAROO_RANKS

    DESCRIPTION

    KANGAROO 17×17 symmetric, valued proximities
    KANGAROO_RANKS 17×2 valued matrix containing two sets of dominance rankings.

    BACKGROUND The KANGAROO file shows frequencies of observed physical proximities among a collection of 17 free-ranging grey kangaroos. Observations were made in the Nadgee Nature Reserve in New South Wales. There were 18 kangaroos in the original report, but one (number M11) was never observed and is therefore dropped from this table.

    The first five row-columns are females, the next 12 are males. F4, F5 and M2 are juveniles.

    Two kinds of dominance ranks are also reported in KANGAROO_RANKS. One, SS, is the ratio of an animal's number of "successes" to its number of "involvements." The other, PS, is calculated by assigning an animal 2 points for each other animal it bests on more than 50% of their contacts. One point is given for a tie and none for less than 50% successes. Since, except for a juvenile male (M2), there were no cross-sex contests, males and females are ranked seperately, but M2 is ranked with the females.

    REFERENCE

  • T. R. Grant, "Dominance and association among members of a captive and a free-ranging group of grey kangaroos (Macropus giganthus)," Animal Behaviour, 1973, 21: 449-456.
  • List of datasets


    GRIMMER--JOINT SENATE PRESS RELEASES

    DATASET JPR

    DESCRIPTION One 92×92 binary matrix.

    BACKGROUND These data are from Justin Grimmer's doctoral dissertation in political science at Harvard. They record instances of joint press releases issued by U. S. Senators.

    REFERENCE

    • http://people.fas.harvard.edu/~jgrimmer/

    List of datasets


    GUHL--HENS PECKING ORDER

    DATASET HENS

    DESCRIPTION One 32×32 non-symmetric binary matrix.

    BACKGROUND The table records the "peck order" of a flock of 32 White Leghorn hens studied in 1946. When a 1 is present, the row hen can peck the column hen. The author claims that temporal changes are rare; once a hen dominates another, that pattern persists.

    REFERENCE

    • Guhl, A. M., 1953. Social Behavior of the Domestic Fowl. Manhattan, Kansas: Kansas State College, Agricultural Experiment Station, Technical Bulletin 73.

    List of datasets


    HAAS--BIGHORN SHEEP DOMINANCE

    DATASETS SHEEP SHEEP_AGES

    DESCRIPTION One 28×28 non-symmetric matrix of frequencies. One 28×1 vector of ages.

    SHEEP non-symmetric, valued
    SHEEP_AGES ages

    BACKGROUND Data record wins and losses for 28 female bighorn sheep observed on the National Bison Range in 1984. The cell entry is the number of occasions on which the row sheep was observed dominating the column sheep. Ages are listed, but those assigned an age of 9 are at least 9 years old; they may be older.

    REFERENCE

    • Christine Hass, "Social status in female bighorn sheep (Ovis canadensis): expression, development and reproductive correlates." Journal of the Zoological Society of London, 1991, 225: 509-523.Station, Technical Bulletin 73.

    List of datasets


    JEONG,MASON,BARABASI,OLTVAI--PROTEIN-PROTEIN INTERACTION

    DATASETS PRO-PRO PRONAM

    DESCRIPTION

    PRO-PRO A binary edgelist in which each lines lists a protein-protein link
    PRONAM A 2114×4 matrix containing the names, groups and lethalities of the proteins.

    BACKGROUND One research area in biology in which centralities have been applied is protein-protein interaction. Interactions between proteins are common. They play an important part in every process involving living cells. Knowledge about how they interact can lead to better understanding of a great many diseases and it can help in the design of appropriate therapies.

    Often studies of protein-protein interaction generate huge data sets. In the letter in Nature that was mentioned above, Jeong, Mason, Barabasi and Oltvai (2001) examined a data matrix that contained interactions linking 2114 proteins contained in yeast. Earlier experimental work had demonstrated that some of the protein molecules in yeast were lethal; if they were removed the yeast would die. Removing others, however, had no such dramatic effect. So Jeong et al. examined the question of whether the structural properties of those proteins, in particular their degree centralities, could predict which proteins were lethal and which ones were not. Their results showed that proteins of high degree were far more likely to be lethal than those of lower degree.

    Subsequent articles (cited below) questioned these results. The argument was that gaps in the data called the whole analysis into question.

    REFERENCES

  • Jeong, H., S. P. Mason, A.-L. Barabasi and Z. N. Oltvai. (2001). "Lethality and centrality in protein networks." Nature 411(6833): 41-42.
  • S. Coulomb, M. Bauer, D. Bernard, and M.-C. Marsolier-Kergoat. (2005). "Gene essentiality and the topology of protein interaction networks", Proceedings of the Royal Society B: Biological Sciences, Volume 272, Number 1573:1721-1725.
  • J.-D. Han, D. Dupuy, N. Bertin, M. E. Cusick, and M. Vidal. (2005). "Effect of sampling on topology predictions of protein-protein interaction networks", Nature Biotechnology 23 (7):839-844.
  • M. Stumpf, C. Wiuf, and R. May. (2005). "Subnets of scale-free networks are not scale-free: Sampling properties of networks", PNAS 102 (12):4221-4224.
  • List of datasets


    KADUSHIN--THE FRENCH FINANCIAL ELITE

    DATASETS FFE FFE_TRAIT

    DESCRIPTION

    FFE: Three 28×28 matrices:

    INFLUENCE non-symmetric, binary.
    ELITE non-symmetric, binary.
    FRIEND symmetric, binary.

    FFE_TRAIT: One 28×24 valued matrix of traits.

    BACKGROUND In 1990 Kadushin collected data from 127 members of the French financial elite. He used various criteria to determine the top 28 and recorded their who-to-whom responses to questions about who was influencential, who were members of the elite and who were friends. He also recorded a large amount of information on their individual backgrounds and characteristics.

    REFERENCE

    • Kadushin, C. 1995. "Friendship among the French financial elite." American Sociological Review 60:202-221.

    List of datasets


    KAPFERER--MINE

    DATASET KAPMINE

    DESCRIPTION Two 15×15 matrices

    KAPFMM symmetric, binary.
    KAPFMU symmetric, binary.

    BACKGROUND Bruce Kapferer (1969) collected data on men working on the surface in a mining operation in Zambia (then Northern Rhodesia). He wanted to account for the development and resolution of a conflict among the workers. The conflict centered on two men, Abraham and Donald; most workers ended up supporting Abraham.

    Kapferer observed and recorded several types of interactions among the workers, including conversation, joking, job assistance, cash assistance and personal assistance. Unfortunately, he did not publish these data. Instead, the matrices indicate the workers joined only by uniplex ties (based on one relationship only, KAPFMU) or those joined by multiple-relation or multiplex ties (KAPFMM).

    REFERENCES

    • Kapferer B. (1969). Norms and the manipulation of relationships in a work context. In J Mitchell (ed), Social networks in urban situations. Manchester: Manchester University Press.
    • Doreian P. (1974). On the connectivity of social networks. Journal of Mathematical Sociology, 3, 245-258.

    List of datasets


    KAPFERER--TAILOR SHOP

    DATASET KAPTAIL

    DESCRIPTION Four 39×39 matrices

    KAPFTS1 symmetric, binary
    KAPFTS2 symmetric, binary
    KAPFTI1 non-symmetric, binary
    KAPFTI2 non-symmetric, binary

    BACKGROUND Bruce Kapferer (1972) observed interactions in a tailor shop in Zambia (then Northern Rhodesia) over a period of ten months. His focus was the changing patterns of alliance among workers during extended negotiations for higher wages.

    The matrices represent two different types of interaction, recorded at two different times (seven months apart) over a period of one month. TI1 and TI2 record the "instrumental" (work- and assistance-related) interactions at the two times; TS1 and TS2 the "sociational" (friendship, socioemotional) interactions.

    The data are particularly interesting since an abortive strike occurred after the first set of observations, and a successful strike took place after the second.

    REFERENCE

    • Kapferer B. (1972). Strategy and transaction in an African factory. Manchester: Manchester University Press.

    List of datasets


    KNUTH--CHARACTERS FROM LES MISERABLES

    DATASET LESMIS

    DESCRIPTION One 77×77 matrix, symmetric, frequencies.

    BACKGROUND The file contains the weighted network of coappearances of characters in Victor Hugo's novel "Les Miserables". Nodes represent characters as indicated by the labels and edges connect any pair of characters that appear in the same chapter of the book. The values on the edges are the number of such coappearances.

    REFERENCE

    • D. E. Knuth. (1993). The Stanford GraphBase: A Platform for Combinatorial Computing, Addison-Wesley, Reading, MA

    List of datasets


    KRACKHARDT--HIGH-TECH MANAGERS

    DATASETS KRACKHT KRACKHT_ATTRIBUTE

    DESCRIPTION KRACKHT Three 21×21 matrices:

    ADVICE non-symmetric, binary.
    FRIENDSHIP non-symmetric, binary.
    REPORTS non-symmetric, binary.
    KRACKHT_ATTRIBUTE: One 21×4 valued matrix

    BACKGROUND These data were collected from the managers of a high-tec company. The company manufactured high-tech equipment on the west coast of the United States and had just over 100 employees with 21 managers. Each manager was asked "To whom do you go to for advice?" and "Who is your friend?" Data for the item "To whom do you report?" was taken from company documents. In addition attribute information was collected. This consisted of the managers age (in years), length of service or tenure (in years), level in the corporate hierarchy (coded 1,2 and 3; 1=CEO, 2 = Vice President, 3 = manager) and department (coded 1,2,3,4 with the CEO in department 0 ie not in a department).

    REFERENCE

    • Krackhardt D. (1987). Cognitive social structures. Social Networks, 9, 104-134.

    List of datasets


    KRACKHARDT--OFFICE COGNITIVE SOCIAL STRUCTURE

    DATASETS

    KRACKAD non-symmetric, binary.
    KRACKFR symmetric, binary.

    DESCRIPTION Each file contains twenty-one 21×21 matrices. Matrix n gives actor n's perception of the whole network.

    BACKGROUND David Krackhardt collected cognitive social structure data from 21 management personnel in a high-tech, machine manufacturing firm to assess the effects of a recent management intervention program. The relation queried was "Who does X go to for advice and help with work?" (KRACKAD) and "Who is a friend of X?" (KRACKFR). Each person indicated not only his or her own advice and friendship relationships, but also the relations he or she perceived among all other managers, generating a full 21 × 21 matrix of adjacency ratings from each person in the group.

    REFERENCE

    • Krackhardt D. (1987). Cognitive social structures. Social Networks, 9, 104-134.

    List of datasets


    KREBS--FORTUNE 500 IT DEPARTMENT

    DATASET KREBS

    DESCRIPTION

    KREBS: Five 56×56 valued matrices:

    BUSINESS_1 non-symmetric, valued.
    BUSINESS_2 non-symmetric, valued.
    ADVICE non-symmetric, valued.
    TECHNICAL non-symmetric, valued.
    CUSTOMER non-symmetric, valued.

    BACKGROUND The data were collected by Valdis Krebs in the IT Deapartment of a Fortune 500 company. Fifty-six individuals were surveyed. The first 7 were administrative staff, The next 12 were together in a department. The next 17 were in a second department. And the following 17 were in a third department. Finally, the last 3 were executives.

    Each individual reported on five different kinds of links:

    1 = With whom do you work with in Business Process 1?
    2 = With whom do you work with in Business Process 2?
    3 = Who do you seek for advice before making a key decision?
    4 = Who do you seek for technical expertise in IT?
    5 = With whom do you discuss customer needs and issues?

    And, for each kind of link, each individual reported the frequency of contact with each of the other individuals:

    1 = Yearly or less
    2 = Quarterly
    3 = Monthly
    4 = Weekly
    5 = Daily or more

    List of datasets


    KREBS--AMAZON POLITICAL BOOKS

    DATASET BOOKS

    DESCRIPTION One 105×105 non-symmetric binary matrix.

    BACKGROUND Nodes represent books about US politics sold by the online bookseller Amazon.com. Edges represent frequent co-purchasing of books by the same buyers, as indicated by the "customers who bought this book also bought these other books" feature on Amazon.

    REFERENCE

    • Valdis Krebs, unpublished, http://www.orgnet.com/.

    List of datasets


    KUTSUKAKE,SUETSUGU,HASEGAWA--GREETING AND GROOMING IN COLOBUS MONKEYS

    DATASETS GandG GandG_ATT

    DESCRIPTION

    BOTT: Two 10×10 matrices:

    GROOMING non-symmetric, valued.
    GREETING non-symmetric, valued.

    GandG_ATT: One 10×2 valued matrix of sex and age grades

    BACKGROUND The authors recorded affiliative behavior linking pairs among individuals in a captive colony of ten black-and-white colobus monkeys. Both grooming and greeting are reported in GandG. Greeting was described as non-sexual mounting. They described it as functioning as a tension-reducing mechanism in nonagonistic situations. Both sex and age grade are contained in GandG_ATT. Females are coded 2, males 1. Three age grades are coded; adults are 3, sub-adults 2 and juveniles 1.

    REFERENCE

    • Kutsukake,N., N. Suetsugu and T. Hasegawa 2006. "Pattern, Distribution, and Function of Greeting Behavior Among Black-and-White Colobus," International Journal of Primatology, 27: 1271-1291.

    List of datasets


    LAZEGA--LAW FIRM

    DATASETS LAZEGA LAZATT

    DESCRIPTION

    LAZEGA: Three 71×71 matrices:

    ADVICE non-symmetric, binary.
    FRIENDSHIP non-symmetric, binary.
    CO-WORK non-symmetric, binary.

    LAZATT: One 71×7 valued matrix.

    BACKGROUND This data set comes from a network study of corporate law partnership that was carried out in a Northeastern US corporate law firm, referred to as SG&R, 1988-1991 in New England. It includes (among others) measurements of networks among the 71 attorneys (partners and associates) of this firm, i.e. their strong-coworker network, advice network, friendship network, and indirect control networks. Various members' attributes are also part of the dataset, including seniority, formal status, office in which they work, gender, lawschool attended. The ethnography, organizational and network analyses of this case are available in Lazega (2001).

    Strong coworkers network:
    "Because most firms like yours are also organized very informally, it is difficult to get a clear idea of how the members really work together. Think back over the past year, consider all the lawyers in your Firm. Would you go through this list and check the names of those with whom you have worked with. [By "worked with" I mean that you have spent time together on at least one case, that you have been assigned to the same case, that they read or used your work product or that you have read or used their work product; this includes professional work done within the Firm like Bar association work, administration, etc.]"

    Basic advice network:
    "Think back over the past year, consider all the lawyers in your Firm. To whom did you go for basic professional advice? For instance, you want to make sure that you are handling a case right, making a proper decision, and you want to consult someone whose professional opinions are in general of great value to you. By advice I do not mean simply technical advice."

    Friendship network:
    "Would you go through this list, and check the names of those you socialize with outside work. You know their family, they know yours, for instance. I do not mean all the people you are simply on a friendly level with, or people you happen to meet at Firm functions."

    Coding:
    The three networks refer to cowork, friendship, and advice. The first 36 respondents are the partners in the firm. The attribute variables in the file LAZATT file.dat are:

    1. status (1=partner; 2=associate)
    2. gender (1=man; 2=woman)
    3. office (1=Boston; 2=Hartford; 3=Providence)
    4. years with the firm
    5. age
    6. practice (1=litigation; 2=corporate)
    7. law school (1: harvard, yale; 2: ucon; 3: other)

    REFERENCES

    • Emmanuel Lazega, The Collegial Phenomenon: The Social Mechanisms of Cooperation Among Peers in a Corporate Law Partnership, Oxford University Press (2001).
    • Tom A.B. Snijders, Philippa E. Pattison, Garry L. Robins, and Mark S. Handcock. New specifications for exponential random graph models. Sociological Methodology (2006), 99-153.

    List of datasets


    LOTT--BISON DOMINANCE

    DATASETS BISON BISON_BREEDING

    DESCRIPTION

    BISON 26×26 non-symmetric, valued dominance encounters
    BISON_BREEDING 26×1 vector reporting number of breeding successes.

    BACKGROUND The usual aggressive behaviors (fighting, nod-threats, broadside threats, head-on threats, rush threats and supplanting) were recorded among 26 males in a herd of American bison. Observations were recorded for 12 hours per day from July 25 through August 14, 1972 on the National Bison Range in Moiese, Montana. In addition, breeding behavior was recorded.

    REFERENCE

  • D. F. Lott, "Dominance relations and breeding rate in mature male American bison," Zeitschrift Tierpsychologie, 1979, 49: 418-432.
  • List of datasets


    LUSSEAU--DOLPHIN GROUPS

    DATASET DOLPHINS

    DESCRIPTION One 62×62 binary matrix.

    BACKGROUND The file dolphins contains an undirected social network recording frequent associations between pairs in a community of 62 dolphins living off Doubtful Sound, New Zealand.

    REFERENCES

    • D. Lusseau, K. Schneider, O. J. Boisseau, P. Haase, E. Slooten, and S. M. Dawson, The bottlenose dolphin community of Doubtful Sound features a large proportion of long-lasting associations, Behavioral Ecology and Sociobiology 54, 396-405 (2003).
    • D. Lusseau, The emergent properties of a dolphin social network, Proc. R. Soc. London B (suppl.) 270, S186-S188 (2003).
    • D. Lusseau, Evidence for social role in a dolphin social network, Preprint q-bio/0607048 (http://arxiv.org/abs/q-bio.PE/0607048)

    List of datasets


    MCCARTY--SOCIAL NETWORKS COAUTHORS

    DATASET AUTH

    DESCRIPTION One 475×475 matrix, symmetric, valued.

    BACKGROUND Chris McCarty prepared a data set for the 2008 INSNA meeting in St. Pete. He recorded all the coauthorships in the Social Networks journal from the beginning to provide a network of networkers. The result was a t-shirt with a graphic design that was sold at the meeting.

    After the meeting, Lin Freeman cleaned the data set and made it available here. It takes the form of a matrix that records coauthorship among 475 authors who were involved in the production of 295 articles. Cell entries report the number of coaurherships displayed by pairs of authors.

    List of datasets


    MCGREW--DOMINANCE AMONG BRITISH PRESCHOOLERS

    DATASET OX_KIDS

    DESCRIPTION One 11×11 non-symmetric valued matrix.

    BACKGROUND W. C. McGrew reported a series of ethological observations of preschool children in Oxford England. One set of observations involved watching boys who were competing for a toy. "Winners" were those who ended up with the toy. Results are presented here.

    REFERENCE

    • McGrew, W. C. 1972. An Ethological Study of Children's Behavior. New York, Academic Press, p. 125.

    List of datasets


    MIZRUCHI--CORPORATE POLITICAL ACTION

    DATASET MIZR

    DESCRIPTION Six 57×57 matrices.

    SAME_STATE symmetric, binary.
    SAME_INDUS symmetric, binary.
    COMM_STKHLDRS symmetric, valued.
    DIR_INTERLKS symmetric, valued.
    INDIR_INTERLKS symmetric, valued.
    JOINT_CONTRIBUTION symmetric, valued.

    BACKGROUND Mark Mizruchi collected these data in the late 1980s. He recorded a great many attributes of major corporations as well as data on their similarities and differences. Six data matrices are reported here. SAME_STATE tallies those pairs of corporations that are headquartered in the same state. SAME_INDUS records those who are in the same industry. COMM_STKHLDRS is the natural logarithm of the number of stockholders that own at least 0.5 percent of the stock in both firms. DIR_INTERLKS is a record of the number of individuals who sit simultaneously on the boards of directors of both firms. INDIR_INTERLKS records the number of leading banks and insurance companies that have interlocks with both firms. And JOINT_CONTRIBUTION is the number of candidates for office who received contributions from both firms.

    REFERENCE Mizruchi, M. The Structure of Corporate Political Action (Harvard University Press, 1992.

    List of datasets


    NEWCOMB,NORDLIE--FRATERNITY

    DATASET NEWFRAT

    DESCRIPTION Fifteen 17×17 matrices.

    NEWC0 - NEWC15 (except NEWC9) non-symmetric, valued (rankings).

    BACKGROUND These 15 matrices record weekly sociometric preference rankings from 17 men attending the University of Michigan in the fall of 1956; data from week 9 are missing. A "1" indicates first preference, and no ties were allowed.

    The men were recruited to live in off-campus (fraternity) housing, rented for them as part of the Michigan Group Study Project supervised by Theodore Newcomb from 1953 to 1956. All were incoming transfer students with no prior acquaintance of one another.

    REFERENCES

    • Newcomb T. (1961). The acquaintance process. New York: Holt, Reinhard & Winston.
    • Nordlie P. (1958). A longitudinal study of interpersonal attraction in a natural group setting. Unpublished doctoral dissertation, University of Michigan.
    • White H., Boorman S. and Breiger R. (1977). Social structure from multiple networks, I. Blockmodels of roles and positions. American Journal of Sociology, 81, 730-780.

    List of datasets


    NEWMAN--NETSCIENCE COAUTHORS

    DATASET NETSCI

    DESCRIPTION One 1589×1589 symmetric, weighted matrix.

    BACKGROUND The file NETSCI contains a coauthorship network of scientists working on network theory and experiment, as compiled by Mark Newman in May 2006. The network was compiled from the bibliographies of two review articles on networks, M. E. J. Newman, SIAM Review 45, 167-256 (2003) and S. Boccaletti et al., Physics Reports 424, 175-308 (2006), with a few additional references added by hand. The version given here contains all components of the network, for a total of 1589 scientists, and not just the largest component of 379 scientists previously published. The network is weighted, with weights assigned directly in terms of the number of collaborations between authors and inversely in terms of the number of other authors involved. This weighting is described in M. E. J. Newman, Phys. Rev. E 64, 016132 (2001).

    REFERENCE

    • M. E. J. Newman, Finding community structure in networks using the eigenvectors of matrices, Preprint physics/0605087 (2006).

    List of datasets


    PADGETT--FLORENTINE FAMILIES

    DATASETS PADGETT and PADGW

    DESCRIPTION PADGETT

    Two 16×16 matrices:

    PADGB symmetric binary
    PADGM symmetric binary
    PADGW

    One 16×3 matrix, valued.

    BACKGROUND Breiger & Pattison (1986), in their discussion of local role analysis, use a subset of data on the social relations among Renaissance Florentine families (person aggregates) collected by John Padgett from historical documents. The two relations are business ties (PADGB - specifically, recorded financial ties such as loans, credits and joint partnerships) and marriage alliances (PADGM).

    As Breiger & Pattison point out, the original data are symmetrically coded. This is acceptable perhaps for marital ties, but is unfortunate for the financial ties (which are almost certainly directed). To remedy this, the financial ties can be recoded as directed relations using some external measure of power - for instance, a measure of wealth. PADGW provides information on (1) each family's net wealth in 1427 (in thousands of lira); (2) the number of priorates (seats on the civic council) held between 1282- 1344; and (3) the total number of business or marriage ties in the total dataset of 116 families (see Breiger & Pattison (1986), p 239).

    Substantively, the data include families who were locked in a struggle for political control of the city of Florence in around 1430. Two factions were dominant in this struggle: one revolved around the infamous Medicis (9), the other around the powerful Strozzis (15).

    REFERENCES

    • Breiger R. and Pattison P. (1986). Cumulated social roles: The duality of persons and their algebras. Social Networks, 8, 215-256.
    • Kent D. (1978). The rise of the Medici: Faction in Florence, 1426-1434. Oxford: Oxford University Press.

    List of datasets


    PARKER,ASHER--CHILDREN'S FRIENDSHIP

    DATASETS

    THIRD THIRD_ATT
    FOURTH FOURTH_ATT
    FIFTH FIFTH_ATT

    DESCRIPTION Friendship is recorded among students in three school classes.
    THIRD is a 22×22 non-symmetric binary matrix,
    FOURTH is a 24×24 non-symmetric binary matrix and
    FIFTH is a 22×22 non-symmetric binary matrix.
    The attribute file (_ATT) associated with each grade gives the sex of each student. Boys are coded as 1, girls as 0.

    BACKGROUND In 1993 Parker and Asher studied elementary school children's friendships. They collected network data from 881 children in 36 classrooms in the third, fourth and fifth grades in five public elementary schools. Each child was given a roster of the children in his or her class and was told to choose his or her 'very best friend', three 'best friends', and an unlimited number of 'friends'.

    Anderson, Wasserman and Crouch chose three of the 36 classrooms, one from each grade. They ignored distinctions among the quality or strength of the reported friendships and simply created one relation reflecting friendship. Thus, if i said that j was either a 'very best friend', 'best friend', or simply 'friend', they coded a 'friendship' tie as being present. Their codes are the ones reported here.

    REFERENCES

  • Anderson, C. J., S. Wasserman and B. Crouch. 1999. "A p* primer: logit models for social networks." Social Networks 21:37-66.
  • Parker, J.G., Asher, S.R., 1993. "Friendship and friendship quality in middle childhood: Links with peer group acceptance and feelings of loneliness and social dissatisfaction." Developmental Psychology 29, 611-621.
  • List of datasets


    ROBINS--AUSTRALIAN BANK

    DATASET BANK

    DESCRIPTION Four 11×11 matrices

    ADVICE-SEEKING non-symmetric, binary
    SATISFYING non-symmetric, binary
    CONFIDING non-symmetric, binary
    CLOSE_FRIENDS non-symmetric, binary

    BACKGROUND These are data from a study by Garry Robins of structure in a number of branches of a large Australian bank. The relations presented are from one branch in response to questions: (1) With whom might you check out a course of action if an issue arises in your work? (the advice-seeking relation); (2) With whom do you feel that your work interactions are particularly satisfying? (the satisfying interaction relation); (3) In whom do you feel you would be able to confide if a problem arose that you did not want everyone to know about? (the confiding relation); (4) Whom do you consider to be a particularly close friend? (the close friend relation). The first listed respondent is the Branch manager, the second is the deputy manager, the third, fourth, and fifth respondents are service advisers (a middle ranking position within the branch), and the remaining respondents are tellers.

    REFERENCE

    • Pattison P., S. Wasserman, G. Robins and A. M. Kanfer. 2000. "Statistical Evaluation of Algebraic Constraints for Social Networks." Journal of Mathematical Psychology, 44: 536-568.

    List of datasets


    RODRIGUEZ--MADRID TRAIN BOMBING

    DATASET TRAIN

    DESCRIPTION One 70×70 symmetric binary matrix.

    BACKGROUND Jose A. Rodriguez of the University of Barcelona created a network of the individuals involved in the bombing of commuter trains in Madrid on March 11, 2004. Rodriguez used press accounts in the two major Spanish daily newspapers (El Pais and El Mundo) to reconstruct the terrorist network. The names included were of those people suspected of having participated and their relatves. Four relations were recorded:

    Rodriguez specified 4 kinds of ties linking theindividuals involved:

    1.Trust--friendship (contact, kinship, links in the telephone center).
    2. Ties to Al Qaeda and to Osama Bin Laden.
    3. Co-participation in training camps and/or wars.
    4. Co-participation in previous terrorist Attacks (Sept 11, Casablanca).

    These four were added together providing a "strength of connection" index that ranges from 1 to 4.

    REFERENCE

    • Hayes, Brian. 2006. "Connecting the dots." American Scientist 94 (5):400-404.

    List of datasets


    ROETHLISBERGER,DICKSON--BANK WIRING ROOM

    DATASET WIRING

    DESCRIPTION Six 14×14 matrices

    RDGAM symmetric, binary
    RDCON symmetric, binary
    RDPOS symmetric, binary
    RDNEG symmetric, binary
    RDHLP non-symmetric, binary
    RDJOB non-symmetric, valued.

    BACKGROUND These are the observational data on 14 Western Electric (Hawthorne Plant) employees from the bank wiring room first presented in Roethlisberger & Dickson (1939). The data are better known through a scrutiny made of the interactions in Homans (1950), and the CONCOR analyses presented in Breiger et al (1975).

    The employees worked in a single room and include two inspectors (I1 and I3), three solderers (S1, S2 and S3), and nine wiremen or assemblers (W1 to W9). The interaction categories include: RDGAM, participation in horseplay; RDCON, participation in arguments about open windows; RDPOS, friendship; RDNEG, antagonistic (negative) behavior; RDHLP, helping others with work; and RDJOB, the number of times workers traded job assignments.

    REFERENCES

    • Breiger R., Boorman S. and Arabie P. (1975). An algorithm for clustering relational data with applications to social network analysis and comparison with multidimensional scaling. Journal of Mathematical Psychology, 12, 328-383.
    • Homans G. (1950). The human group. New York: Harcourt-Brace.
    • Roethlisberger F. and Dickson W. (1939). Management and the worker. Cambridge: Cambridge University Press.

    List of datasets


    ROMHILD,HARRISON--PROPER NOUNS IN THE KING JAMES BIBLE

    DATASET NAMES

    DESCRIPTION One 1773×1773 symmetric valued matrix stored as an edgelist.

    BACKGROUND Christoph Romhild recorded 1773 proper nouns--people and places--in the King James Bible. He tallied 63,779 occasions in which pairs of these proper nouns appeared in the same verse in the bible. Many of these, of course, appeared more than once. So the data presented here are tallies, for each pair of proper nouns, of the number of verses in which they appeared together. Romhild worked with Chris Harrison, and together, they produced some elegant visual images of the data. They are displayed in the source listed below.

    REFERENCE

    • http://chrisharrison.net/projects/bibleviz/index.html

    List of datasets


    ROSENFELD,WHITE--ST. LOUIS CRIME

    DATASETS CRIME SEX

    DESCRIPTION One 870×557 two mode valued matrix of individuals by involvement in crime events. One 870×1 vector displaying the sex of each individual.

    CRIME two mode, valued
    SEX vector reporting sex of each individual.

    BACKGROUND In the 1990s Rick Rosenfeld and Norm White used police records to collect data on crime in St. Louis. They began with five homicides and recorded the names of all the individuals who had been involved as victims, suspects or witnesses. They then explored the files and recorded all the other crimes in which those same individuals appeared. This snowball process was continued until they had data on 557 crime events. Those events involved 870 participants of which: 569 appeared as victims 682 appeared as suspects 195 appeared as witnesses, and 41 were dual (they were recorded both as victims and suspects in the same crime. Their data appear, then, as an 870 by 557, individual by crime event matrix. Victims are coded as 1, suspects as 2, witnesses as 3 and duals as 4.
    In addition Rosenfeld and White recorded the sex of each individual.

    List of datasets


    ROSENGREN--SWEDISH LITERARY CRITICISM

    DATASET SWEDISH

    DESCRIPTION One 15×15 matrix, symmetric, binary.

    BACKGROUND Rosengren collected data on Swedish literary critics writing during the stylistic revolution in Swedish literature in 1881 to 1883. He recorded sets of authors, other than the author being reviewed, who were mentioned together in any published literary review in the Swedish press during those years. Then he dropped any pairs that were mentioned together less than five times and he included only those pairs of authors whose proportion of co-mentions was more than three standard errors above its expectation.

    REFERENCES

    • Rosengren, K. E. (1968). Sociological Aspects of the Literary System. Stockholm: Natur och Culture.
    • Rosengren, K. E. (1983). The Climate of Literature: Sweden's Literary Frume of Reference, 1953-1976. Lund: Studentlitteratur.
    • Freeman, Linton C. "Boxicity and the Social Context of Swedish Literary Criticism, 1881-1883." Journal of Social and Biological Structures, 9, 1986, 141-149.

    List of datasets


    SADE--RHESUS MONKEY GROOMING

    DATASET RHESUS

    DESCRIPTION One 16×16 matrix, non-symmetric, frequencies.

    BACKGROUND Table of observed grooming episodes in a community of free ranging rhesus monkeys in Cayo Santiago observed in June and July of 1963. Seven are males (066, ER, R006, EZ, EC, CY and CN) and the other nine are females.

    REFERENCE

    • D. S. Sade, "Sociometrics of Macaca mulatta: Linkages and cliques in grooming matrices," Folia Primatologica, 1972, 18: 196-223.

    List of datasets


    SAMPSON--MONASTERY

    DATASET SAMPSON

    DESCRIPTION Ten 18×18 matrices

    SAMPLK1 non-symmetric, valued (rankings)
    SAMPLK2 non-symmetric, valued (rankings)
    SAMPLK3 non-symmetric, valued (rankings)
    SAMPDLK non-symmetric, valued (rankings)
    SAMPES non-symmetric, valued (rankings)
    SAMPDES non-symmetric, valued (rankings)
    SAMPIN non-symmetric, valued (rankings)
    SAMPNIN non-symmetric, valued (rankings)
    SAMPPR non-symmetric, valued (rankings)
    SAMPNPR non-symmetric, valued (rankings)

    BACKGROUND Sampson recorded the social interactions among a group of monks while resident as an experimenter on vision, and collected numerous sociometric rankings. During his stay, a political "crisis in the cloister" resulted in the expulsion of four monks (Nos. 2, 3, 17, and 18) and the voluntary departure of several others - most immediately, Nos. 1, 7, 14, 15, and 16. (In the end, only 5, 6, 9, and 11 remained).

    Most of the present data are retrospective, collected after the breakup occurred. They concern a period during which a new cohort entered the monastery near the end of the study but before the major conflict began. The exceptions are "liking" data gathered at three times: SAMPLK1 to SAMPLK3 - that reflect changes in group sentiment over time (SAMPLK3 was collected in the same wave as the data described below). Information about the senior monks was not included.

    Four relations are coded, with separate matrices for positive and negative ties on the relation. Each member ranked only his top three choices on that tie. The relations are esteem (SAMPES) and disesteem (SAMPDES), liking (SAMPLK) and disliking (SAMPDLK), positive influence (SAMPIN) and negative influence (SAMPNIN), praise (SAMPPR) and blame (SAMPNPR). In all rankings 3 indicates the highest or first choice and 1 the last choice. (Some subjects offered tied ranks for their top four choices).

    REFERENCES

    • Breiger R., Boorman S. and Arabie P. (1975). An algorithm for clustering relational data with applications to social network analysis and comparison with multidimensional scaling. Journal of Mathematical Psychology, 12, 328-383.
    • Sampson, S. (1969). Crisis in a cloister. Unpublished doctoral dissertation, Cornell University.

    List of datasets


    SCHEIN,FOHRMAN--CATTLE DOMINANCE

    DATASET CATTLE

    DESCRIPTION One 28×28 matrix, non-symmetric, valued.

    BACKGROUND Here the data report part of the observations of dominance-deference behavior exhibited by a herd of dairy cattle at the Iberia Livestock Experiment Station in Jenerette, Louisiana. Contests (most of which were merely threats) were recorded and winners were recorded. The table shows the number of occasions on which the row cow bested the column cow.

    REFERENCE

    • M. W. Schein & M. H. Fohrman, "Social dominance relationships in a herd of dairy cattle," 1955, British Journal of Animal Behaviour, 3: 45-55.

    List of datasets


    SCHWIMMER--TARO EXCHANGE

    DATASET TARO

    DESCRIPTION One 22×22 matrix, symmetric, binary.

    BACKGROUND These data represent the relation of gift-giving (taro exchange) among 22 households in a Papuan village. Hage & Harary (1983) used them to illustrate a graph hamiltonian cycle. Schwimmer points out how these ties function to define the appropriate persons to mediate the act of asking for or receiving assistance among group members.

    REFERENCES

    • Hage P. and Harary F. (1983). Structural models in anthropology. Cambridge: Cambridge University Press.
    • Schwimmer E. (1973). Exchange in the social structure of the Orokaiva. New York: St Martins.

    List of datasets


    SMITH,WHITE--INTERNATIONAL TRADE

    DATASETS TRADE TRADE_ATTRIBUTE

    DESCRIPTION

    TRADE: Five 24×24 matrices:

    MANUFACTURED_GOODS non-symmetric, binary.
    FOODS non-symmetric, binary.
    CRUDE_MATERIALS non-symmetric, binary.
    MINERALS non-symmetric, binary.
    DIPLOMATIC_EXCHANGE non-symmetric, binary.

    TRADE_ATTRIBUTE: One 24×4 valued matrix

    BACKGROUND These data were selected by Wasserman and Faust (1994) from a list of 63 countries given by Smith and White (1988). The selection was intended to be a representative sample of countries which spanned the globe physically, economically and politically and was used by them in their network analysis book. The data records interaction of the countries with respect to trade of four goods, namely:manufactured goods, food and live animals, crude materials (not food) and minerals and fuels. The final matrix records exchange of diplomats between the countries. All trade (including the diplomats) is from the row to the column. The Trade_Attribute data lists average population growth between 1970 and 1981, average GNP growth (per capita) over the same period, secondary school enrollment ratio in 1981, and energy consumption in 1981 (in kilo coal equivalents per capita).

    REFERENCES

    • Smith D and D White (1988). Structure and dynamics of the global economy: Network analysis of international trade 1965-1980. Unpublished Manuscript.
    • Wasserman S and K Faust (1994). Social Network Analysis: Methods and Applications.Cambridge University Press, Cambridge.

    List of datasets


    STOKMAN,ZIEGLER,SCOTT--CORPORATE INTERLOCKS

    DATASETS SZCID, SZCIG

    DESCRIPTION

    SZCID: One 16×16 matrix, symmetric, binary.
    SZCIG: One 15×15 matrix, symmetric, binary.

    BACKGROUND These data come from a six-year research project, concluded in 1976, on corporate power in nine European countries and the United States. Each matrix represents corporate interlocks among the major business entities of two countries - the Netherlands (SZCID) and West Germany (SZCIG).

    The volume describing this study, referenced below, includes six chapters on network theoretical and analytical issues related to data of this type.

    REFERENCES

    • Ziegler R., Bender R. and Biehler H. (1985). Industry and banking in the German corporate network. In F. Stokman, R. Ziegler & J. Scott (eds), Networks of corporate power. Cambridge: Polity Press, 1985.
    • Stokman F., Wasseur F. and Elsas D. (1985). The Dutch network: Types of interlocks and network structure. In F. Stokman, R. Ziegler & J. Scott (eds), Networks of corporate power. Cambridge: Polity Press, 1985.

    List of datasets


    STRAYER,CUMMINS--DOMINANCE AMONG SUB-ADULT MACAQUES

    DATASET MACAQUE1

    DESCRIPTION Two 16×16 matrices.

    AGGRESSION non-symmetric, valued.
    COMPETITION non-symmetric, valued.

    BACKGROUND The two tables report dominance encounters in a colony of 16 subadult and juvenile macaque monkeys (Macaca nemestrina) at the Washington Regional Primate Center in Seattle. The first matrix is a record of the number of times the row monkey expressed agressive behaviors (i.e. assault, bite, push-pull, pout-threat, lunge-threat, chase) that resulted in the column monkey showing clear submission (rapid flight, fear-grimace, cringe, withdraw). Individuals are tagged with gender labels; Numbers are males and letters are females.

    The second matrix is a record of competition for an object or to occupy a space. A "win" was tabulated when the row monkey got the contested object or occupied the space.

    REFERENCE

    • F. F. Strayer and Mark S. Cummins, "Aggressive and competitive structures in captive monkey groups," in Donald R. Omary, F. F. Strayer and Daniel G. Freedman, Dominance Relations: An Ethological View of Human Conflict and Social Interaction. New York, Garland STPM Press, 1980, pp. 85-96.

    List of datasets


    STRAYER,CUMMINS--DOMINANCE AMONG ADULT MACAQUES

    DATASET MACAQUE2

    DESCRIPTION One 30×30 matrix of dominance encounters.

    BACKGROUND This matrix is built from experimental data on the 30 adult members (5 males and 25 females) of a community of macaque monkeys (Macaca mulatta) housed at the Wisconsin Regional Primate Center in Madison. The monkeys were deprived of water and then observations of which monkey got access to a drinking fountain were made.

    The data were converted into an index of consistency in linear dominance rankings for six month-long experimental periods. The index is not clearly presented. Individuals are identified with gender tags; Numbers are males, letters are females.

    REFERENCE

    • F. F. Strayer and Mark S. Cummins, "Aggressive and competitive structures in captive monkey groups," in Donald R. Omark, F. F. Strayer and Daniel G. Freedman, eds., Dominance Relations: An Ethological View of Human Conflict and Social Interaction. New York: Garland STPM Press, 1980, pp. 85-96.

    List of datasets


    STRAYER,STRAYER,CHAPESKIE--PRESCHOOL DOMINANCE

    DATASETS PRE_1 PRE_2

    DESCRIPTION Two communities of preschoolers. One is a 17×17 non-symmetric matrix of frequencies and the other is a 19×19 non-symmetric matrix of frequencies.

    PRE_1 non-symmetric, valued dominance
    PRE_2 non-symmetric, valued dominance

    BACKGROUND The data are based on observations of 17 and 19 preschool children in two different settings. in Waterloo, Ontario. They show the results of interaction leading to submission on the part of one child or the other.

    REFERENCES

  • Strayer, F.F. and Janet Strayer. 1976. "An Ethological Analysis of Social Agonism and Dominance Relations among Preschool Children." Child Development. 47:980-989.
  • Strayer, F. F., Janet Strayer and Thomas R. Chapeskie. 1980. "The perception of social power among preschool children." Chapter 10 in Ormack, Donald R., F. F. Strayer and Daniel G. Freedman (eds.), Dominance Relations. New York: Garland STPM Press.
  • List of datasets


    SUNDARESAN,FISCHOFF,DUSHOFF,RUBENSTEIN--ZEBRA AFFILIATION

    DATASETS ZEBRA ZEBATT

    DESCRIPTION

    ZEBRA 28×28 symmetric, valued affiliation matrix
    ZEBATT 28×1 vector where 1=lactating female, 2= non-lactating female and 3=male.

    BACKGROUND This matrix is based on a study of a community of 28 Grevy's zebras. Cell entries of 1 indicate that a pair of zebras appeared together at least once during the study. Entries of 2 indicate a statistically significant tendency of pairs to appear together.
    The authors show that Grevy's zebra individuals form tightly knit cliques which themselves occasionally associate. As demonstrated in past studies, they confirmed that Grevy's zebra females are selective in their choices of associates, tending to form bonds with others in the same reproductive state.

    REFERENCE

  • Sundaresan, S. R., I. R. Fischhoff, J. Dushoff and D. I. Rubenstein. 2007. "Network metrics reveal diVerences in social organization between two Wssion-fusion species, Grevy's zebra and onager." Oecologia 151:140-149.
  • List of datasets


    TAKAHATA--MACAQUE DOMINANCE

    DATASET MAC

    DESCRIPTION One 62×62 matrix of dominance encounters.

    BACKGROUND The matrix records dominance of the row animal over the column animal in a colony of 62 adult female Japanese macaques (Macaca fuscata fuscata). They are known as the "Arashiyama B group." Records were made during the non-mating season, April to early October, 1976. Approach-retreat episodes involving food were recorded.

    In addition, the presence of six lineages was reported. The first 4 animals belong to a lineage, and the next 14 belong to another. The following 31 are in a third lineage, and the next 6 are in the fourth. The following 6 are the fifth lineage, and the remaining animal is unrelated to the others.

    REFERENCE

    • Y. Takahata, "Diachronic changes in the dominance relations of adult female Japanese monkeys of the Arashiyama B group," in Linda Marie Fedigan and Pamela J. Asquith, eds., The Monkeys of Arashiyama. Albany: State University of New York Press, 1991, pp. 124-139.

    List of datasets


    UDRY,HARRIS--ADOLESCENT HEALTH NETWORKS

    DATASETS Linked list formats of friendship choices made by students from 84 communities. Each community contains either 1 or two junior high or high schools. The numbers of students in each community vary. Those numbers range from 25 to 2587. In each case the data include friendship choices and various individual characteristics.

    COMM 1 and COMM 1_ATTCOMM 2 and COMM 2_ATTCOMM 3 and COMM 3_ATT
    COMM 4 and COMM 4_ATTCOMM 5 and COMM 5_ATTCOMM 6 and COMM 6_ATT
    COMM 7 and COMM 7_ATTCOMM 8 and COMM 8_ATTCOMM 9 and COMM 9_ATT
    COMM10 and COMM10_ATTCOMM11 and COMM11_ATTCOMM12 and COMM12_ATT
    COMM13 and COMM13_ATTCOMM14 and COMM14_ATTCOMM15 and COMM15_ATT
    COMM16 and COMM16_ATTCOMM17 and COMM17_ATTCOMM18 and COMM18_ATT
    COMM19 and COMM19_ATTCOMM20 and COMM20_ATTCOMM21 and COMM21_ATT
    COMM22 and COMM22_ATTCOMM23 and COMM23_ATTCOMM24 and COMM24_ATT
    COMM25 and COMM25_ATTCOMM26 and COMM26_ATTCOMM27 and COMM27_ATT
    COMM28 and COMM28_ATTCOMM29 and COMM29_ATTCOMM30 and COMM30_ATT
    COMM31 and COMM31_ATTCOMM32 and COMM32_ATTCOMM33 and COMM33_ATT
    COMM34 and COMM34_ATTCOMM35 and COMM35_ATTCOMM36 and COMM36_ATT
    COMM37 and COMM37_ATTCOMM38 and COMM38_ATTCOMM39 and COMM39_ATT
    COMM40 and COMM40_ATTCOMM41 and COMM41_ATTCOMM42 and COMM42_ATT
    COMM43 and COMM43_ATTCOMM44 and COMM44_ATTCOMM45 and COMM45_ATT
    COMM46 and COMM46_ATTCOMM47 and COMM47_ATTCOMM48 and COMM48_ATT
    COMM49 and COMM49_ATTCOMM50 and COMM50_ATTCOMM51 and COMM51_ATT
    COMM52 and COMM52_ATTCOMM53 and COMM53_ATTCOMM54 and COMM54_ATT
    COMM55 and COMM55_ATTCOMM56 and COMM56_ATTCOMM57 and COMM57_ATT
    COMM58 and COMM58_ATTCOMM59 and COMM59_ATTCOMM60 and COMM60_ATT
    COMM61 and COMM61_ATTCOMM62 and COMM62_ATTCOMM63 and COMM63_ATT
    COMM64 and COMM64_ATTCOMM65 and COMM65_ATTCOMM66 and COMM66_ATT
    COMM67 and COMM67_ATTCOMM68 and COMM68_ATTCOMM69 and COMM69_ATT
    COMM70 and COMM70_ATTCOMM71 and COMM71_ATTCOMM72 and COMM72_ATT
    COMM73 and COMM73_ATTCOMM74 and COMM74_ATTCOMM75 and COMM75_ATT
    COMM76 and COMM76_ATTCOMM77 and COMM77_ATTCOMM78 and COMM78_ATT
    COMM79 and COMM79_ATTCOMM80 and COMM80_ATTCOMM81 and COMM81_ATT
    COMM82 and COMM82_ATTCOMM83 and COMM83_ATTCOMM84 and COMM84_ATT

    DESCRIPTION

    The ADD HEALTH data are constructed from the in-school questionnaire; 90,118 students representing 84 communities took this survey in 1994-95. Some communities had only one school; others had two. Where there are two schools in a community students from one school were allowed to name friends in the other, the "sister school."

    Each student was given a paper-and-pencil questionnaire and a copy of a roster listing every student in the school and, if the community had two schools, the student s provided with the roster of the "sister" school. The name generator asked about five male and five female friends separately. The question was, "List your closest (male/female) friends. List your best (male/female) friend first, then your next best friend, and so on. (girls/boys) may include (boys/girls) who are friends and (boy/girl) friends."
    For each friend named, the student was asked to check off whether he/she participated in any of five activities with the friend. These activities were:

    1. you went to (his/her) house in the last seven days.
    2. you met (him/her) after school to hang out or go somewhere in the last seven days.
    3. you spent time with (him/her) last weekend.
    4. you talked with (him/her) about a problem in the last seven days.
    5. you talked with (him/her) on the telephone in the last seven days.

    These activities were summed to create a valued network. Ties range in value from 1, meaning the student nominated the friend but reported no activities, to 6, meaning the student nominated the friend and reported participating in all five activities with the friend.

    Because nominations to friends in the sister school were allowed, the networks here are reported at the community level. When two schools were present in a community the data file includes a node-level indicator for school code, so one can easily extract choices from the separate schools.

    The friendship choices are recorded in the COMM files. And the COMM_ATT files include the sex, race, grade in school and, in communities that have two schools, the school code.

    Sex is coded 1=male, 2=female, 0=unreported. Race is coded 1=white, 2=black, 3=hispanic, 4=asian, 5=mixed/other, 0=unreported. Grade is recorded as a number between 7 and 12 with 0=unreported. And school codes are 0 and 1 when two schools were in a single community.

    REFERENCE

    • Moody, James, "Peer influence groups: identifying dense clusters in large networks," Social Networks, 2001, 23: 261-283.

    List of datasets


    VAN DE BUNT--DUTCH COLLEGE FRESHMEN

    DATASETS VDB VDBATT

    DESCRIPTION

    Seven 32×32 matrices:

    TIME_0 non-symmetric, valued.
    TIME_1 non-symmetric, valued.
    TIME_2 non-symmetric, valued.
    TIME_3 non-symmetric, valued.
    TIME_4 non-symmetric, valued.
    TIME_5 non-symmetric, valued.
    TIME_6 non-symmetric, valued.

    VDBATT: One 32×3 valued matrix

    BACKGROUND This data set was collected by Gerhard van de Bunt, and is discussed extensively in van de Bunt (1999) and van de Bunt, van Duijn, and Snijders (1999). The data were collected among a group of university freshmen who, except for a few existing relationships (acquaintances from a former school), did not know each other at the first measurement (time=t0). The data were collected at 7 time points. The first four time points are three weeks apart, whereas the last three time points are six weeks apart. The original group consisted of 49 students, but due to 'university drop-outs' and after deleting those who did not fill in the questionnaire four or more times, a group was obtained of 32 students for whom almost complete data are available.

    The students were asked to rate their relationships on a six point scale, with response categories described as follows.

    1. Best friendship Persons whom you would call your 'real' friends
    2. Friendship Persons with whom you have a good relationship, but whom you do not (yet) consider a 'real' friend
    3. Friendly relationship Persons with whom you regularly have pleasant contact during classes. The contact could grow into a friendship
    4. Neutral relationship Persons with whom you have not much in common. In case of an accidental meeting the contact is good. The chance of it growing into a friendship is not large
    0. Unknown person Persons whom you do not know
    5. Troubled relationship Persons with whom you can't get on very well, and with whom you definitely do not want to start a relationship. There is a certain risk of getting into a conflict

    Available individual characteristics are sex, education program, and smoking behavior. Smoking was only allowed in special areas. As a consequence, the 'smokers' had to separate themselves from the 'non-smokers' if they wished to smoke (which they often did during coffee and lunch breaks). Thus, contact opportunities differed between actors because of their smoking behavior. The education program was important because, although all started to study at the same moment, there were three groups, following different courses. During the first months all programs overlapped largely, but after a few months, the programs diverged. Especially the 2-year program was quite different from the other two programs. Therefore, this attribute also gives information on the individuals' contact opportunities.

    The digraph data files are TIME_0 to TIME_6. The networks are coded as 6 = item non-response, 9 = actor non-response. Note that 6 and 9 are missing data codes.

    The actor attributes are in the file vdbatt.dat. Variables are, respectively, gender (1 = F, 2 = M), program (2-year, 3-year, 4-year), and smoking (1 = yes, 2 = no). See the references listed below for further information about this network and the actor attributes.

    REFERENCES

    • Van de Bunt, G.G. 1999. Friends by choice. An actor-oriented statistical network model for friendship networks through time. Amsterdam: Thesis Publishers.
    • Van de Bunt, G.G., M.A.J. van Duijn, and T.A.B. Snijders. 1999. Friendship networks through time: An actor-oriented statistical network model. Computational and Mathematical Organization Theory, 5, 167-192.

    List of datasets


    VAN HOOFF,WENSING--WOLF DOMINANCE

    DATASETS WOLF WOLF_ATT

    DESCRIPTION

    One 16×16 matrix of frequencies. One 16×2 matrix revealing ages and sexes (Males are coded 1).

    WOLF frequencies.
    WOLF_ATT wolves ages and sexes.

    BACKGROUND These are data on a captive family of wolves in Arnheim, Germany. The 16 wolves studied here were housed in a large wooded enclosure and observed in 1978. This matrix displays deference acts. The number in a cell represents the number of occasions on which the row wolf was seen to exhibit a "low posture" display directed toward the column wolf. The behavior could involve approach or retreat, but the fact that it was performed in "low posture" suggests that it was deferent.

    REFERENCE

    • Jan A. R. A. M. van Hooff and Joep A. B. Wensing, "Dominance and its behavioral measures in a captive wolf pack," Chapter 11 in Harry Frank, ed., Man and Wolf. Dordrecht: Junk, 1987, pp. 219-252.

    List of datasets


    VICKERS,CHAN--SEVENTH GRADERS

    DATASET SEVENTH

    DESCRIPTION Three 29×29 matrices.

    GET_ON non-symmetric, binary.
    BEST_FRIENDS non-symmetric, binary.
    WORK_WITH non-symmetric, binary.

    BACKGROUND The data were collected by Vickers from 29 seventh grade students in a school in Victoria, Australia. Students were asked to nominate their classmates on a number of relations including the following three:

    Who do you get on with in the class?
    Who are your best friends in the class?
    Who would you prefer to work with?

    Stidents 1 through 12 are boys and 13 through 29 are girls.

    REFERENCEs

    • Robins, G., P. Pattison and S. Wasserman. 1999. "Logit models and logistic regressions for social networks:III. Valued relations." Psychometrika 64: 371-394.
    • Vickers, M. and S. Chan. 1981. Representing Classroom Social Structure. Melbourne: Victoria Institute of Secondary Education.
    • Wasserman, S. and P. Pattison. 1996. "Logit models and logistic regressions for social networks: I. An introduction to Markov graphs and p*." Psychometrika 61: 401-425.

    List of datasets


    WATTS,STROGATZ--NEURAL NETWORK

    DATASET ELEGANS

    DESCRIPTION One 306×306 frequency matrix stored as an edgelist.

    BACKGROUND This data set describs the neural network of the worm Caenorhabditis elegans. The first column is the "from" vertex. The second column is the "to" vertex. The third column is the number of links (i.e. the weight of the edge). Multiple rows with the same number in the first column correspond to multiple edges for the same vertex. The network is therefore a weighted, directed, graph.

    REFERENCE

    • Watts, D.J.; Strogatz, S.H. (1998). "Collective dynamics of 'small-world' networks.". Nature 393 (6684): 409-10.

    List of datasets


    WEBSTER--ACCOUNTING FIRM

    DATASETS ACCT ACC_ATT

    DESCRIPTION

    ACCT: Four 24×24 matrices:

    OBSERVED_SOCIAL_1 symmetric, valued.
    OBSERVED_WORK symmetric, valued.
    REPORTED_SOCIAL non-symmetric, valued.
    REPORTED_WORK non-symmetric, valued.

    ACC_ATT: One 24×2 matrix:
    Column 1, sex (1 = male. 2 = femle
    Column 2, job (1 = Partner, 2 = Manager, 3 = Accountant, 4 = Staff member

    BACKGROUND In 1991 and 1992 Cinthia Webster collected data on both work ties and social ties from 24 members of a small accounting firm. Six respondents were partners in the firm, three were managers, nine were staff accounts and the other six were support staff.

    First, ad libitum sampling was used to observe social interactions in a wide range of settings. This produced the OBSERVED_SOCIAL matrix. Work assignment sheets were used to determine who had worked with whom and they produced the OBSERVED_WORK data. Then each individual was asked to report others with whom he or she had socialized and those with whom they had worked. REPORTED_SOCIAL and REPORTED_WORK coded responses to these questions.

    REFERENCES

    • Webster, C. M. (1993). Task-related and context-based constraints in observed and reported relational data. Doctoral Dissertation, University of California, Irvine.
    • Webster, C. M. (1995). "Detecting context-based constraints in social perception." Journal of Quantitative Anthropology, 5:285-303.

    List of datasets


    WEBSTER--RESIDENCE HALL FRIENDSHIP

    DATASET OZ

    DESCRIPTION One 217×217 matrix of tie strengths.

    BACKGROUND Cynthia Webster collected friendship data among the 217 residents living at a residence hall located on the Australian National University campus. Residents were interviewed individually at the start of the second semester.

    First, they were asked to recall all of their friends who currently lived in the residence hall. They then were provided with a list of all residents and were asked to add anyone whom they also considered a friend, but had forgotten to include. From the complete list of friends, they were asked to indicate the strength of each friendship tie. Most specified three levels of friendship, "best friend," "close friend," and "friend." The data were combined to form a valued, actor-by-actor matrix of reported friendship relations.

    REFERENCE

    • L. C. Freeman, C. M. Webster and D. M. Kirke (1998) "Exploring social structure using dynamic three-dimensional color images." Social Networks 20, 109-118

    List of datasets


    WELLMAN--INSNA TEACHER-STUDENT

    DATASET TS

    DESCRIPTION One 60×60 matrix, non-symmetric, binary.

    BACKGROUND When Barry Wellman founded the International Network for Social Network Analysis (INSNA) in 1977, he sent a questionnaire to all the founding members. Included were questions on who taught each founder and who each founder taught. This data set is based on their responses.

    REFERENCE

    • K. Reitz and D. R. White, 1989 "Rethinking the Role Concept: Homomorphisms on Social Networks" pp. 429-488 in L.C.Freeman, D.R. White, A.K.Romney, eds., Research Methods in Social Network Analysis. George Mason Press. Reprinted 1992 Transaction Publishers: New Brunswick, NJ.

    List of datasets


    ZACHARY--KARATE CLUB

    DATASET ZACHARY

    DESCRIPTION Two 34×34 matrices.

    ZACHE symmetric, binary.
    ZACHC symmetric, valued.

    BACKGROUND These are data collected from the members of a university karate club by Wayne Zachary. The ZACHE matrix represents the presence or absence of ties among the members of the club; the ZACHC matrix indicates the relative strength of the associations (number of situations in and outside the club in which interactions occurred).

    Zachary (1977) used these data and an information flow model of network conflict resolution to explain the split-up of this group following disputes among the members.

    REFERENCE

    • Zachary W. (1977). An information flow model for conflict and fission in small groups. Journal of Anthropological Research, 33, 452-473.

    List of datasets