The game of contacts: Estimating the social visibility of groups

Estimating the sizes of hard-to-count populations is a challenging and important problem that occurs frequently in social science, public health, and public policy. This problem is particularly pressing in HIV/AIDS research because estimates of the sizes of the most at-risk populations-illicit drug users, men who have sex with men, and sex workers-are needed for designing, evaluating, and funding programs to curb the spread of the disease. A promising new approach in this area is the network scale-up method, which uses information about the personal networks of respondents to make population size estimates. However, if the target population has low social visibility, as is likely to be the case in HIV/AIDS research, scale-up estimates will be too low. In this paper we develop a game-like activity that we call the game of contacts in order to estimate the social visibility of groups, and report results from a study of heavy drug users in Curitiba, Brazil (n = 294). The game produced estimates of social visibility that were consistent with qualitative expectations but of surprising magnitude. Further, a number of checks suggest that the data are high-quality. While motivated by the specific problem of population size estimation, our method could be used by researchers more broadly and adds to long-standing efforts to combine the richness of social network analysis with the power and scale of sample surveys.

[1]  Laura A. Dabbish,et al.  Designing games with a purpose , 2008, CACM.

[2]  M. McPherson,et al.  Birds of a Feather: Homophily in Social Networks , 2001 .

[3]  Ronald S. Burt,et al.  Network items and the general social survey , 1984 .

[4]  Winter A. Mason,et al.  Real and perceived attitude agreement in social networks. , 2010, Journal of personality and social psychology.

[5]  Eric R. Ziegel,et al.  Survey Errors and Survey Costs , 1990 .

[6]  Peter V. Marsden,et al.  Interviewer effects in measuring network size using a single name generator , 2003, Soc. Networks.

[7]  Christopher McCarty,et al.  Eliciting representative samples of personal networks , 1997 .

[8]  J. Coleman Relational Analysis: The Study of Social Organizations with Survey Methods , 1958 .

[9]  Mark S Handcock,et al.  7. Respondent-Driven Sampling: An Assessment of Current Methodology , 2009, Sociological methodology.

[10]  Matthew J. Salganik,et al.  Respondent‐driven sampling as Markov chain Monte Carlo , 2009, Statistics in medicine.

[11]  H. Russell Bernard,et al.  Who knows your HIV status? What HIV + patients and their network members know about each other , 1995 .

[12]  H. Russell Bernard,et al.  A social network approach to estimating seroprevalence in the United States , 1998 .

[13]  Mark S. Granovetter Network Sampling: Some First Steps , 1976, American Journal of Sociology.

[14]  Robert M. Groves,et al.  Survey Nonresponse , 2002 .

[15]  Tian Zheng,et al.  How Many People Do You Know in Prison? , 2006 .

[16]  P. Killworth,et al.  The Problem of Informant Accuracy: The Validity of Retrospective Data , 1984 .

[17]  H. Russell Bernard,et al.  Who Knows Your HIV Status II?: Information Propagation Within Social Networks of Seropositive People , 2006 .

[18]  J. Kitts Egocentric bias or information management? Selective disclosure and the social roots of norm misperception , 2003 .

[19]  T. Tilburg,et al.  Interviewer Effects in the Measurement of Personal Network Size A Nonexperimental Study , 1998 .

[20]  L. Ross,et al.  The “false consensus effect”: An egocentric bias in social perception and attribution processes , 1977 .

[21]  Matthew J. Salganik,et al.  How Many People Do You Know?: Efficiently Estimating Personal Network Size , 2010, Journal of the American Statistical Association.

[22]  Matthew J. Salganik,et al.  Counting hard-to-count populations: the network scale-up method for public health , 2010, Sexually Transmitted Infections.

[23]  Seymour Sudman,et al.  Measurement errors in surveys , 1993 .

[24]  Claude S. Fischer,et al.  A Procedure for Surveying Personal Networks , 1978 .

[25]  Norman Miller,et al.  Ten years of research on the false-consensus effect: an empirical and theoretical review , 1987 .

[26]  Erik M. Volz,et al.  Probability based estimation theory for respondent driven sampling , 2008 .

[27]  F. I. Bastos,et al.  Taxas de Infecção de HIV e Sífilis e Inventário de Conhecimento, Atitudes e Práticas de Risco Relacionadas Às Infecções Sexualmente Transmissíveis Entre Usuários de Drogas em 10 Municípios Brasileiros , 2009 .

[28]  C. McCarty,et al.  Comparing Two Methods for Estimating Network Size , 2001 .

[29]  H. Russell Bernard,et al.  Estimation of Seroprevalence, Rape, and Homelessness in the United States Using a Social Network Approach , 1998, Evaluation review.

[30]  K. Konda,et al.  Estimating the number of men who have sex with men in low and middle income countries , 2006, Sexually Transmitted Infections.

[31]  E. Laumann,et al.  Friends of Urban Men: An Assessment of Accuracy in Reporting Their Socioeconomic Attributes, Mutual Choice, and Attitude Agreement , 2016 .

[32]  Devon D. Brewer,et al.  Forgetting in the recall-based elicitation of personal and social networks , 2000, Soc. Networks.

[33]  H. Russell Bernard,et al.  A social network approach to corroborating the number of AIDS/HIV+ victims in the US ° , 1995 .

[34]  H. Russell Bernard,et al.  Estimating the size of an average personal network and of an event subpopulation: Some empirical results☆ , 1991 .

[35]  Matthew J. Salganik Variance Estimation, Design Effects, and Sample Size Calculations for Respondent-Driven Sampling , 2006, Journal of Urban Health.

[36]  E. Goffman Stigma; Notes On The Management Of Spoiled Identity , 1964 .

[37]  P. V. Marsden,et al.  NETWORK DATA AND MEASUREMENT , 1990 .

[38]  Mohsen Malekinejad,et al.  Implementation Challenges to Using Respondent-Driven Sampling Methodology for HIV Biological and Behavioral Surveillance: Field Experiences in International Settings , 2008, AIDS and Behavior.

[39]  Kevin White,et al.  Accuracy, stability and reciprocity in informal conversational networks in rural Kenya , 2000, Soc. Networks.

[40]  Mohsen Malekinejad,et al.  Using Respondent-Driven Sampling Methodology for HIV Biological and Behavioral Surveillance in International Settings: A Systematic Review , 2008, AIDS and Behavior.

[41]  H. Ward,et al.  Still waiting: poor access to sexual health services in the UK , 2006, Sexually Transmitted Infections.

[42]  Christopher McCarty,et al.  Impact of methods for reducing respondent burden on personal network structural measures , 2007, Soc. Networks.

[43]  Barry Wellman,et al.  Visualizing Personal Networks: Working with Participant-aided Sociograms , 2007 .

[44]  T. Gilovich,et al.  The illusion of transparency: biased assessments of others' ability to read one's emotional states. , 1998, Journal of personality and social psychology.

[45]  Jeffrey Levine,et al.  The Dynamics of Collective Deliberation in the 1996 Election: Campaign Effects on Accessibility, Certainty, and Accuracy , 2000, American Political Science Review.

[46]  D. Brewer,et al.  The social structural basis of the organization of persons in memory , 1995, Human nature.

[47]  Allen H. Barton,et al.  Survey Research and Macro-Methodology , 1968 .

[48]  Cyprian Wejnert,et al.  3. An Empirical Test of Respondent-Driven Sampling: Point Estimates, Variance, Degree Measures, and Out-of-Equilibrium Data , 2009, Sociological methodology.

[49]  H. Russell Bernard,et al.  Investigating the Variation of Personal Network Size Under Unknown Error Conditions , 2006 .

[50]  Mohsen Malekinejad,et al.  Implementation Challenges to Using Respondent-Driven Sampling Methodology for HIV Biological and Behavioral Surveillance: Field Experiences in International Settings , 2008, AIDS and Behavior.

[51]  Douglas D. Heckathorn,et al.  Respondent-driven sampling : A new approach to the study of hidden populations , 1997 .

[52]  Matthew J. Salganik,et al.  Assessing respondent-driven sampling , 2010, Proceedings of the National Academy of Sciences.

[53]  Matthew J. Salganik,et al.  Web-Based Experiments for the Study of Collective Social Dynamics in Cultural Markets , 2009, Top. Cogn. Sci..

[54]  S. T. Buckland,et al.  An Introduction to the Bootstrap. , 1994 .

[55]  Douglas D. Heckathorn,et al.  Respondent-driven sampling II: deriving valid population estimates from chain-referral samples of hi , 2002 .