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UC SAN DIEGO CENTER ON GENDER EQUITY AND HEALTH Using social network analysis to understand social norms Background Social norms refer to attitudes and behaviors that are not only prevalent in a society but are also socially dependent1. Social network studies offer invaluable insights into norms by demonstrating how the attitudes and behaviors of socially connected individuals are correlated2, including those specific to gender equity, maternal, child and reproductive health3. Figure 1. The social ecological model is a framework for understanding the reciprocal relationship between individuals and the social contexts within which they are nested. Social network analysis is an essential part of understanding many of these dynamics. Figure 2. Each square or circle represents an individual and the lines represent social ties. Networks are typically comprised of many individuals with many ties. This allows researchers to understand the structure of the social context and the relationships and characteristics of the individuals within it. Social network Definition: A web of social relationships and their corresponding properties Structural properties of the network Individual position within the network Social influence from person to person Instrumental for helping to: Identify sources of social inequity Uncover possible pathways for social change Understanding barriers to change The connectedness of a network can provide insights into the mechanisms of social norms Identify the strongholds of social norms Figure 3. Depending on the question asked, networks can represent very different types of relationships, with implications for intervention strategies. Here women are represented by circles and men are represented by squares4. References 1.) 2.) 3.) 4.) Bicchieri C, Muldoon R. Social Norms. In: Zalta EN, ed. Stanford Encyclopedia of Philosophy. Spring 2011 ed. Stanford CA: The Metaphysics Research Lab 2011. Multiple sources Kohler HP, Behrman JR, Watkins SC. The density of social networks and fertility decisions: Evidence from South Nyanza District, Kenya. Demography 2001; 38(1): 43-58 Shakya H.B, Christakis N.A., & Fowler J.H. ( 2014) An exploratory comparison of name generator content: data from rural India. Social Networks, 48 (2017) 157-168. doi.org/10.1016/j.socnet.2016.08.008 UC SAN DIEGO CENTER ON GENDER EQUITY AND HEALTH Interesting findings from Center Social Networks research Figure 1a: This figure shows the network of adolescent girls from a US school. The larger the node, the greater the behavioral risk factors for sexual violence. The clustering of those nodes provides structural evidence of risk environments in which sexual violence is more likely. Figure 2b. This shows clusters of socially connected people within one Indian village. Square nodes own toilets; round nodes do not. Note the different distribution of toilet ownership within each group. This suggests that the village is not necessarily the best social unit to target for interventions, but that understanding the context within the village can be vital. Figure 3c shows one village in Honduras network from 2 perspectives. The left panel depicts all ties from a randomly selected group of individuals. Note that intimate partner violence (IPV) acceptance is clustered among socially connected individuals and that IPV is generally more accepted on the periphery of the network. The right panel depicts only within household ties from the same randomly selected group. Note the strong clustering of IPV norms at the household level. a Shakya HB, Fariss C, Ojeda C, Raj A, Reed L.Social network clustering of sexual violence experienced by adolescent girls. (revise and resubmit: American Journal of Epidemiology Shakya HB, Christakis NA, Fowler JH. (2014) Social network communities are associated with health behavior: an observational sociocentric network study of latrine ownership in rural India. American Journal of Public Health. 2014; 104(5)930-937. c Shakya HB, Hughes DA, Stafford DK, Christakis NA, Fowler JH, Silverman JG. (2016) Intimate partner violence norms cluster within households: an observational social network study in rural Honduras. BMC Public Health. PMCID: PMC4782313. doi: 10.1186/s12889-016-28934 b