Volume 25, Issue 1, 2003
|Ties & Bonds, 4-5|
|StOCNET: Software for the statistical analysis of social networks, 7-26|
Huisman, Mark, Duijn, Marijtje A.J. van
StOCNET3 is an open software system in a Windows environment for the advanced statistical analysis of social networks. It provides a platform to make a number of recently developed and therefore not (yet) standard statistical methods available to a wider audience. A flexible user interface utilizing an easily accessible data structure is developed such that new methods can readily be included in the future. As such, it will allow researchers to develop new statistical tools by combining their own programs with routines of the StOCNET system, providing a faster availability of newly developed methods. In this paper we show the current state of the developments. The emphasis is on the implementation and operation of the programs that are included in StOCNET: BLOCKS (for stochastic blockmodeling), p2 (for analyzing binary network data with actor and/or dyadic covariates), SIENA (for analyzing repeated measurements of social networks), and ZO (for calculating probability distributions of statistics). Moreover, we present an overview of future contributions, which will be available in the near future, and of planned activities with respect to the functionality of the StOCNET software. StOCNET is a freeware PC program, and can be obtained from the StOCNET website at http://stat.gamma.rug.nl/stocnet/.
|Note on Network Sampling in Drug Abuse Research, 27-35|
Spreen, Marinus, Coumans, Moniek
In this article we discuss a network sampling design that can be applied in drug abuse research at the community level. At this level often some partial sampling frame such as the register of a drug aid agency is available. This partial sampling frame can be used as the start of a network sample. Each selected registered drug abuser mentions his relationships with other drug abusers, and from those newly mentioned drug abusers who are not registered a second probability sample is drawn. Using this network sampling design the mean contact rates between clients, between clients and non registered drug abusers and between non registered drug abusers can be estimated despite the unknown total number of drug abusers. The design is illustrated by an analysis of the network data of the Heerlen Drug Monitoring System.
|Visualizing Complexity Networks: Seeing Both the Forest and the Trees, 37-47|
McGrath, Cathleen, Krackhardt, David, Blythe, Jim
Visualization of complex relational information has become increasingly important as complex data and computational power have become more available to social network researchers. Common sources of relational complexity include change over time, multiple relationships, network size, and network density. The most useful method for displaying complex data often depends upon the source of complexity and the nature of the information to be learned. In this paper, we explore the use of motion, especially for representation of change over time and relationship. Also, using data from a large Wall Street investment bank, we demonstrate several strategies to represent complex relational data in two-dimensions.
|Hyperlink Network Analysis: A New Method for the Study of Social Structure on the Web, 49-61|
Park, Han Woo
This paper identifies hyperlink network analysis (HNA) as a newly emerging methodology. It suggests that social (or communication) structures on the web may be analyzed based on the hyperlinks among websites. Hyperlink network analysis has advantages in describing emerging structures among social actors on the web. In order to examine what constitutes hyperlink network analysis, this paper reviews prior research on the topic. Further, it describes the data-gathering techniques for those interested in hyperlink network analysis.
|Abstracts - Sunbelt 2002, 63-112|
|Abstracts - Books, Chapters, Articles, 113-130|
Volume 25, Issue 2, 2003
|A Network PIoneer has Passed Away, 1|
|Ties & Bonds, 2-5|
|Social Network Influences on Adolescent Substance Use: An Introduction, 11-16|
Valente, Thomas W.
|Predisposition and Pressure: Mutual Influence and Adolescent Drunkenness, 17-31|
Many explanations of adolescent alcohol use patterns rely on a combination of individual, family, and peer influences to explain transitions and levels of use. Peer use of alcohol is often found to be the most important predictor of an adolescent’s own use of alcohol. The predominant inference drawn from this consistent finding is that an adolescent’s peers influence him or her to use alcohol. A methodological limitation of these studies is that they rely on information from only one member of the friendship pair. I posit that the traditional psychosocial model gives an incomplete understanding of the peer influence process. This study uses the sociometric design of the National Longitudinal Study of Adolescent Health (Add Health) to demonstrate that adolescent friends influence one another to establish and maintain alcohol use patterns over time. I estimate the effect of mutual peer influence in the context of a broader model of adolescent alcohol use that controls for individual background factors of each friend. The mutual influence process demonstrated in cross-sectional analysis persists in two longitudinal model specifications that control for prior behavioral similarity between the friends.
|Peer Network, Sensation Seeking, and Drug Use Among Junior and Senior High School Students , 32-58|
Rice, Ronald E., Donohew, Lewis, Clayton, Richard
This study argues that both individual and social factors are strong influences on use of drugs by adolescents and teenagers, and, further, that these factors may interact. Thus, both individual and social factors offer avenues for targeting prime at-risk groups and designing messages and programs to reach them. The primary individual factors explored here are prior drug use, attitudes toward drug use, closeness toward family, susceptibility to peer pressure, and sensation-seeking, and the social factors explored are the attitudes, behaviors, and sensation-seeking of respondents’ named friends/peers. In particular, peers’ own responses are used instead of respondents’ estimated or perceived peers’ drug attitudes, behaviors and sensation-seeking. These factors are included in a model that is tested over three cohorts of an average of 1900 junior- and high-school students, each measured at three successive grades. Both one’s own sensation-seeking, and peer influence (their drug use, and their sensationseeking), along with one’s own prior drug use, are the main predictors of specific drug use at the end of the periods.
|Drifting Smoke Rings: Social Network Analysis and Markov Processes in a Longitudinal Study of Friendship Groups and Risk-taking, 59-76|
Pearson, Michael, West, Patrick
Social network analysis is applied to three time points of a longitudinal study, which examines how risk-taking (represented by smoking and cannabis use) in adolescence is associated with social position within peer group structures. One hundred and fifty two students in the second year of secondary education in one Scottish school named up to six best friends, allowing for the categorization of each adolescent as a group member, a group peripheral or a relative isolate. Building on previous work, it is shown that transitions from non risk-taking to risk-taking behavior occur predominantly at peer group, rather than peripheral or isolate membership level. The transitions of pupils from time point one through to time point three are modeled as a Markov process, based on the assumption that the social position and risk-taking behavior (or transitional state) of a pupil at a certain time point depends only on their state at the previous time point. The results show that the Markov process is not stationary. The expected length of time spent by pupils in the various transitional states is also modeled, and provides another (time) dimension to the influence of peers on risk-taking behavior. We hypothesize that the influence exercised by an individual in a social network context increases with the cohesiveness of the individual’s social network position and the length of time he or she occupies that position. The results testify to the importance of risk-taking peer groups, both as a source of influence and selection of peripheral members, and to the need for differential targeting by sociometric state when delivering health education and intervention programs.
|Boundary-crossing and Drug Use among Young Adults in a Low-income, Minority, Urban Neighborhood, 77-87|
Flom, Peter L., Friedman, Samuel R., Neaigus, Alan, Sandoval, Milagros
This paper examines the relationship between boundary-crossing sexual partnerships (i.e., those between partners who are 5 or more years older, of a different race or ethnicity, or live in a different neighborhood or borough) and use of crack or injected drugs among young adults in Bushwick, Brooklyn. Women who smoked crack or injected drugs were more likely to have a sexual partner who was older, of a different race/ethnicity, or from a different borough than were women who did not use these drugs; men who used these drugs were more likely to have older sex partners than men who did not. Young people who use these drugs are known to be at higher risk of having HIV and a number of other sexually-transmittable infections such as hepatitis B, genital herpes, and syphilis. The results of this paper imply this risk may be even higher for people who cross these these boundaries. In addition, if these young people become infected, they may be particularly likely to serve as a gateway for spreading infection to other social groups.
|Will You Remember Me In The Morning? Test-Retest Reliability of a Social Network Analysis Examining HIV-Related Risky Behavior in Urban Adolescents and Young Adults, 88-97|
Clair, Scott, Schensul, Jean J., Raju, Monika, Stanek, Edward, Pino, Raul
In recent years there has been a growing interest in applying social network models to the problem of adolescent substance use. However, there has been little research conducted examining the reliability of social network information within this population. The current study attempts to address this gap, specifically by examining social network test-retest reliability over a two week period among a sample of adolescent substance users. The results of the current study suggest that for social network variables dealing with substance use, reliabilities are at least moderate with correlations of .6 or above. However, there is a large degree of turnover with regards to the specific individuals being named in the network with only 62% of alters mentioned at Time 1 being mentioned at Time 2.
|Translating INSNA, 98-117|
Richards, Bill, Sozanski, Tad
A collection of email messages I received between September 10 and November 1, 2003; a clear demonstration of how little I know about the languages spoken by the readers of Connections; a multilingual trip around an international network; an interesting – and instructive – commentary on languages and the difficulties faced by those who want to move from one to another.
INSNA is the professional association for researchers interested in social network analysis. The association is a non-profit organization incorporated in the state of Delaware and founded in 1977.
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