networkdata: Repository of Network Datasets

#' Political Blogs
#' @description 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.

#' @format igraph object
#' @source http://moreno.ss.uci.edu/data.html#blogs
#' @references 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)
"polblogs"


#' Giraffe Affiliation
#' @description  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.
#' @details The three different relations (affil, proximity and neighbor) are given in the relation edge attribute.
#' @format igraph object
#' @source http://moreno.ss.uci.edu/data.html#giraffe
#' @references 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.
"giraffe"


#' Bernard/Killworth - Fraternity (interaction)
#' @description  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.
#' @format igraph object
#' @source http://moreno.ss.uci.edu/data.html#bkfrat
#' @seealso [bkfrac]
#' @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.
"bkfrab"

#' Bernard/Killworth - Fraternity (rankings)
#' @description  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.
#' @format igraph object
#' @source http://moreno.ss.uci.edu/data.html#bkfrat
#' @seealso [bkfrab]
#' @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.
"bkfrac"

#' Bernard/Killworth - Office (interaction)
#' @description  These data concern interactions in a small business office, 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.
#' @format igraph object
#' @source http://moreno.ss.uci.edu/data.html#bkoff
#' @seealso [bkoffc]
#' @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.
"bkoffb"

#' Bernard/Killworth - Office (rankings)
#' @description  These data concern interactions in a small business office, 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.
#' @format igraph object
#' @source http://moreno.ss.uci.edu/data.html#bkoff
#' @seealso [bkoffb]
#' @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.
"bkoffc"

#' Bernard/Killworth - Tech company (interaction)
#' @description  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.
#' @format igraph object
#' @source http://moreno.ss.uci.edu/data.html#bktec
#' @seealso [bktecc]
#' @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.
"bktecb"

#' Bernard/Killworth - Tech company (rankings)
#' @description  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.
#' @format igraph object
#' @source http://moreno.ss.uci.edu/data.html#bktec
#' @seealso [bktecb]
#' @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.
"bktecc"

#' Preschool
#' @description  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.
#' @details The five different relations are given in the relation edge attribute.
#' @format igraph object
#' @source http://moreno.ss.uci.edu/data.html#bott
#' @references
#' Bott, H. "Observations of play activities in a nursery school," *Genetic Psychology Monographs*, 1928, 4: 44-88.
"bott"

#' Pony
#' @description  weights are the number of occasions in which the row pony threatened the column pony.
#' @format igraph object
#' @source http://moreno.ss.uci.edu/data.html#pony
#' @references
#' T.H.Cluton-Brock, J.P.Greenwood and R.P.Powell, 1976, "Ranks and Relationships in Highland Ponies and Highland Cows," *Zeitschrift 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).
"pony"

#' Ant Colony (I)
#' @description  These are observations of ritual dominance activities in an ant community (a collection of 16 female Leptothorax allardycei ants over 18.2 hours in a queenright colony)
#' @format igraph object
#' @source http://moreno.ss.uci.edu/data.html#ants
#' @seealso [ants_2]
#' @references
#' B. J. Cole, 1981, "Dominance hierarchies in Leptothorax ants" *Science*, 212: 83-84.
"ants_1"

#' Ant Colony (II)
#' @description  These are observations of ritual dominance activities in an ant community (a collection of 13 female Leptothorax allardycei ants in a queenless colony)
#' @format igraph object
#' @source http://moreno.ss.uci.edu/data.html#ants
#' @seealso [ants_1]
#' @references
#' B. J. Cole, 1981, "Dominance hierarchies in Leptothorax ants" *Science*, 212: 83-84.
"ants_2"

#' Friendships among High School Boys
#' @description 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.
#' @details the edge attribute time contains the time period.
#' @format igraph object
#' @source http://moreno.ss.uci.edu/data.html#high
#' @references
#' Coleman, J. S. Introduction to Mathermatical Sociology. New York: Free Press, pp.450-451.
"highschool_boys"

#' Innovations among Physicians
#' @description 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.
#' @details
#' The codes are:
#'City: 1 Peoria, 2 Bloomington, 3 Quincy, 4 Galesburg
#'\preformatted{
#'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
#'}
#' @format igraph object
#' @source http://moreno.ss.uci.edu/data.html#ckm
#' @references
#' Coleman, J. S. Introduction to Mathermatical Sociology. New York: Free Press, pp.450-451.
"physicians"

#' Dolphins (I)
#' @description 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.
#' @format igraph object
#' @source http://moreno.ss.uci.edu/data.html#dolphin
#' @references
#' 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.
"dolphins_1"

#' Dolphins (II)
#' @description  undirected social network recording frequent associations between pairs in a community of 62 dolphins living off Doubtful Sound, New Zealand.
#' @format igraph object
#' @source http://moreno.ss.uci.edu/data.html#dolphins
#' @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)
"dolphins_2"

#' Davis - Southern Women
#' @description  These data were collected by Davis et al. in the 1930s. They represent observed attendance at 14 small social events by 18 Southern women.
#' @format (bipartite) igraph object
#' @source http://moreno.ss.uci.edu/data.html#davis
#' @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.

"southern_women"

#' Windsurfers (Interactions)
#' @description  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.
#' @format igraph object
#' @source http://moreno.ss.uci.edu/data.html#beach
#' @seealso [surfersc]
#' @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.
"surfersb"

#' Windsurfers (Closeness)
#' @description  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 (see [surfersb]). 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.
#' @format igraph object
#' @source http://moreno.ss.uci.edu/data.html#beach
#' @seealso [surfersb]
#' @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.
"surfersc"

#' EIES (relations)
#' @description  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).
#'
#' 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.

#' @format igraph object
#' @source http://moreno.ss.uci.edu/data.html#eies
#' @seealso [eies_messages]
#' @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.
"eies_relations"

#' EIES (Messages)
#' @description  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.
#'
#' 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.
#' @format igraph object
#' @source http://moreno.ss.uci.edu/data.html#eies
#' @seealso [eies_relations]
#' @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.
"eies_messages"

#' Ceo's and Clubs
#' @description 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.
#' @format (bipartite) igraph object
#' @source http://moreno.ss.uci.edu/data.html#galas
#' @references
#' Galaskiewicz J (1985). Social Organization of an Urban Grants Economy. New York. Academic Press.
"ceos_clubs"

#' Collaboration in Jazz
#' @description 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.
#' @format igraph object
#' @source http://moreno.ss.uci.edu/data.html#jazz
#' @references
#' 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.
"jazz"

#' Kangaroo
#' @description 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 network.
#'
#'Two kinds of dominance ranks are included. 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.
#' @format igraph object
#' @source http://moreno.ss.uci.edu/data.html#kangaroo
#' @references
#' 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.
"kangaroo"

#' Hens Pecking order
#' @description Records the "peck order" of a flock of 32 White Leghorn hens studied in 1946. A tie from hen a to b means that hen a can peck hen b. The author claims that temporal changes are rare; once a hen dominates another, that pattern persists.
#' @format igraph object
#' @source http://moreno.ss.uci.edu/data.html#hens
#' @references
#' Guhl, A. M., 1953. Social Behavior of the Domestic Fowl. Manhattan, Kansas: Kansas State College, Agricultural Experiment Station, Technical Bulletin 73.
"hens"

#' Joint Senate Press Releases
#' @description 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.
#' @format igraph object
#' @source http://moreno.ss.uci.edu/data.html#jpr
#' @references
#' http://people.fas.harvard.edu/~jgrimmer/
"jpr"

#' Bighorn Sheep Dominance
#' @description Data record wins and losses for 28 female bighorn sheep observed on the National Bison Range in 1984. the weight of a tie from a to b is the number of occasions on which a was observed dominating b. Ages are listed, but those assigned an age of 9 are at least 9 years old; they may be older.
#' @format igraph object
#' @source http://moreno.ss.uci.edu/data.html#sheep
#' @references
#' 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.
"sheep"

#' Protein-Protein Interactions (probably yeast)
#' @description
#' 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.
#' @format igraph object
#' @source http://moreno.ss.uci.edu/data.html#pro-pro
#' @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.
"protein"

#' French Financial Elite (influence)
#' @description 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.
#' @format igraph object
#' @source http://moreno.ss.uci.edu/data#ffe
#' @seealso [ffe_elite],[ffe_friends]
#' @references
#' Kadushin, C. 1995. "Friendship among the French financial elite." *American Sociological Review* 60:202-221.
"ffe_influence"

#' French Financial Elite (elite)
#' @description 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.
#' @format igraph object
#' @source http://moreno.ss.uci.edu/data#ffe
#' @seealso [ffe_influence],[ffe_friends]
#' @references
#' Kadushin, C. 1995. "Friendship among the French financial elite." *American Sociological Review* 60:202-221.
"ffe_elite"

#' French Financial Elite (friendships)
#' @description 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.
#' @format igraph object
#' @source http://moreno.ss.uci.edu/data#ffe
#' @seealso [ffe_influence],[ffe_elite]
#' @references
#' Kadushin, C. 1995. "Friendship among the French financial elite." *American Sociological Review* 60:202-221.
"ffe_friends"

#' Kapferer - Mine
#' @description 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. Two miners are connected if they are connected by any of these relations.
#' @format igraph object
#' @source http://moreno.ss.uci.edu/data#kapmine
#' @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.
"mine"


#' Kapferer - Tailor-Shop (work)
#' @description 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.
#'
#'Kapferer recorded two two different types of interaction, recorded at two different times (seven months apart) over a period of one month. This network includes the"instrumental" (work- and assistance-related) interactions at the two times
#'
#'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.
#'
#' @format igraph object
#' @source http://moreno.ss.uci.edu/data#kaptail
#' @seealso [tailor_social]
#' @references
#' Kapferer B. (1972). Strategy and transaction in an African factory. Manchester: Manchester University Press.
"tailor_work"

#' Kapferer - Tailor-Shop (social)
#' @description 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.
#'
#'Kapferer recorded two two different types of interaction, recorded at two different times (seven months apart) over a period of one month. This network includes 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.
#'
#' @format igraph object
#' @source http://moreno.ss.uci.edu/data#kaptail
#' @seealso [tailor_work]
#' @references
#' Kapferer B. (1972). Strategy and transaction in an African factory. Manchester: Manchester University Press.
"tailor_social"

#' Les Miserables co-appearances
#' @description  Weighted network of co-appearances 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.
#' @format igraph object
#' @source http://moreno.ss.uci.edu/data#lesmis
#' @references
#' D. E. Knuth. (1993). The Stanford GraphBase: A Platform for Combinatorial Computing, Addison-Wesley, Reading, MA
"miserables"

#' High-tech Managers (Advice)
#' @description 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).
#' @format igraph object
#' @source http://moreno.ss.uci.edu/data#krackht
#' @seealso [ht_friends],[ht_reports]
#' @references
#' Krackhardt D. (1987). Cognitive social structures. *Social Networks*, 9, 104-134.
"ht_advice"

#' High-tech Managers (Friendships)
#' @description 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).
#' @format igraph object
#' @source http://moreno.ss.uci.edu/data#krackht
#' @seealso [ht_advice],[ht_reports]
#' @references
#' Krackhardt D. (1987). Cognitive social structures. *Social Networks*, 9, 104-134.
"ht_friends"

#' High-tech Managers (Reports to)
#' @description 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).
#' @format igraph object
#' @source http://moreno.ss.uci.edu/data#krackht
#' @seealso [ht_advice],[ht_friends]
#' @references
#' Krackhardt D. (1987). Cognitive social structures. *Social Networks*, 9, 104-134.
"ht_reports"

#' Political Books
#' @description 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.
#' @format igraph object
#' @source http://moreno.ss.uci.edu/data#books
#' @references
#' Valdis Krebs, unpublished, http://www.orgnet.com/
"polbooks"

#' Law Firm (Advice)
#' @description 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).
#'
#' **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."
#'
#'\preformatted{
#'Coding:
#'The first 36 respondents are the partners in the firm. The attribute variables 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)
#'}
#' @format igraph object
#' @source http://moreno.ss.uci.edu/data#lazega
#' @seealso [law_friends],[law_cowork]
#' @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.
"law_advice"

#' Law Firm (Friendship)
#' @description 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).
#'
#'**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."
#'
#'\preformatted{
#'Coding:
#'The first 36 respondents are the partners in the firm. The attribute variables 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)
#'}
#' @format igraph object
#' @source http://moreno.ss.uci.edu/data#lazega
#' @seealso [law_advice],[law_cowork]
#' @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.
"law_friends"

#' Law Firm (Co-work)
#' @description 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.)"
#'\preformatted{
#'Coding:
#'The first 36 respondents are the partners in the firm. The attribute variables 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)
#'}
#' @format igraph object
#' @source http://moreno.ss.uci.edu/data#lazega
#' @seealso [law_advice],[law_friends]
#' @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.
"law_cowork"

#' Social Networks Coauthors
#' @description  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 on his website. 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.
#' @format igraph object
#' @source http://moreno.ss.uci.edu/data#auth
"sn_auth"

#' Newcomb Fraternity
#' @description  The networksrecord 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.

#' After the meeting, Lin Freeman cleaned the data set and made it available on his website. 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.
#' @format list of 15 igraph objects
#' @source http://moreno.ss.uci.edu/data#newfrat
#' @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.
"fraternity"

#' Netscience Coauthorship
#' @description 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).
#' @format igraph object
#' @source http://moreno.ss.uci.edu/data#netsci
#' @references
#' M. E. J. Newman, Finding community structure in networks using the eigenvectors of matrices, Preprint physics/0605087 (2006).
"netsci"

#' Florentine Families (Business)
#' @description 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 (specifically, recorded financial ties such as loans, credits and joint partnerships) and marriage alliances.
#'
#' 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).
#' @format igraph object
#' @source http://moreno.ss.uci.edu/data#padgett
#' @seealso [flo_marriage]
#' @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.
"flo_business"

#' Florentine Families (Marriage)
#' @description 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 (specifically, recorded financial ties such as loans, credits and joint partnerships) and marriage alliances.
#'
#' 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).
#' @format igraph object
#' @source http://moreno.ss.uci.edu/data#padgett
#' @seealso [flo_business]
#' @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.
"flo_marriage"

#' Madrid Train Bombing
#' @description
#' \preformatted{
#' 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.
#' }
#' @format igraph object
#' @source http://moreno.ss.uci.edu/data#train
#' @references
#'Hayes, Brian. 2006. "Connecting the dots." *American Scientist* 94 (5):400-404.
"train"

#' Bank Wiring Room
#' @description 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.
#'
#' **The dataset only includes the positive and negative ties, making it a signed network**
#' @format igraph object
#' @source http://moreno.ss.uci.edu/data#wiring
#' @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.
"wiring"

#' Nouns in the King's James Bible
#' @description 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.
#' @format igraph object
#' @source http://moreno.ss.uci.edu/data#bible
#' @references
#' http://chrisharrison.net/projects/bibleviz/index.html
"bible"

#' St. Louis Crimes
#' @description 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.
#' @format (bipartite) igraph object
#' @source http://moreno.ss.uci.edu/data#crime
"crime"

#' Swedish Literary Criticism
#' @description 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.
#' @format igraph object
#' @source http://moreno.ss.uci.edu/data#swedish
#' @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.
"literary"

#' Rhesus Monkey Grooming
#' @description 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.
#' @format igraph object
#' @source http://moreno.ss.uci.edu/data#rhesus
#' @references
#' D. S. Sade, "Sociometrics of Macaca mulatta: Linkages and cliques in grooming matrices," *Folia Primatologica*, 1972, 18: 196-223.
"rhesus"

#' Monastery
#' @description  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).
#' @details the different relations are given in a list of networks in the same order as given in the description.
#' @format list of igraph objects
#' @source http://moreno.ss.uci.edu/data#sampson
#' @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.
"sampson"

#' Taro Exchange
#' @description 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.
#' @format igraph object
#' @source http://moreno.ss.uci.edu/data#taro
#' @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.
"taro"

#' Macaque Dominance
#' @description records dominance relations (a directed tie from a to b means a dominates b) 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.
#' @format igraph object
#' @source http://moreno.ss.uci.edu/data#mac
#' @references
#' 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.
"macaque"

#' Residence Hall Friendship
#' @description 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.
#' @format igraph object
#' @source http://moreno.ss.uci.edu/data#oz
#' @references
#' 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
"hall"

#' INSNA Teacher Student
#' @description 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.
#' @format igraph object
#' @source http://moreno.ss.uci.edu/data#ts
#' @references
#' 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.
"insna"

#' Karate Club (binary)
#' @description These are data collected from the members of a university karate club by Wayne Zachary (presence or absence of ties among the members of the club)
#'
#' 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.
#' @format igraph object
#' @source http://moreno.ss.uci.edu/data#zachary
#' @seealso [karate_weight]
#' @references
#' Zachary W. (1977). An information flow model for conflict and fission in small groups. *Journal of Anthropological Research*, 33, 452-473.
"karate"

#' Karate Club (weighted)
#' @description These are data collected from the members of a university karate club by Wayne Zachary (relative strength of the associations, i.e. 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.
#' @format igraph object
#' @source http://moreno.ss.uci.edu/data#zachary
#' @seealso [karate]
#' @references
#' Zachary W. (1977). An information flow model for conflict and fission in small groups. *Journal of Anthropological Research*, 33, 452-473.
"karate_weight"