An exploratory comparison of name generator content: Data from rural India

Abstract

Since the 1970s sociologists have explored the best means for measuring social networks, although few name generator analyses have used sociocentric data or data from developing countries, partly because sociocentric studies in developing countries have been scant. Here, we analyze 12 different name generators used in a sociocentric network study conducted in 75 villages in rural Karnataka, India. Having unusual sociocentric data from a non-Western context allowed us to extend previous name generator research through the unique analyses of network structural measures, an extensive consideration of homophily, and investigation of status difference between egos and alters. We found that domestic interaction questions generated networks that were highly clustered and highly centralized. Similarity between respondents and their nominated contacts was strongest for gender, caste, and religion. We also found that domestic interaction name generators yielded the most homogeneous ties, while advice questions yielded the most heterogeneous. Participants were generally more likely to nominate those of higher social status, although certain questions, such as who participants talk to uncovered more egalitarian relationships, while other name generators elicited the names of social contacts distinctly higher or lower in status than the respondent. Some questions also seemed to uncover networks that were specific to the cultural context, suggesting that network researchers should balance local relevance with global generalizability when choosing name generators.

Keywords: Homophily; India; Name generators; Social hierarchy; Social networks; Social norms; Sociocentric.

Fig. 1

A histogram of out-going nominations for the full network including ties elicited from all 12 name generators.

Fig. 2

Network maps for one sample village, each comparing nominations from two networks in the dataset. It is clear from the first plot that using the condensed network retains much of the full network while substantially reducing the number of questions asked (from 12 down to 7). The subsequent 3 plots show the degree of overlap between nominations in specific name generators. While nominations from invite home and visit their home overlapped significantly, the nominations generated by take advice from and give rice to, for example, were substantially different.

Fig. 3

Plot of the correlation matrix of nominations by name generator (see Table SA 2 for specific values). A hierarchical clustering algorithm was used to reveal conceptual groups that are labeled and color-coded.

Fig. 4

This figure shows the mean difference between alters and egos in-degree measure for each name generator. Across all 12 name generators, egos nominated alters with higher in-degree scores than themselves, as predicted by the “friendship paradox” (Feld, 1991). Name generators with the lowest differences between egos and alters can be categorized as low status questions, those around the median can be categorized as peer questions, and those at the upper end as high status questions. Fig. SA 3 plots these differences against select demographic trait differences.

Fig. 5

Using an average of the homophily measures calculated for each trait across all 12 name generators, we compared the degree to which nominations within any one trait were homophilic. Here we see that by farthe most homophilic traits were demographic while behavioral traits, although also homophilic, were much less so.

Fig. 6

An overview of the degree to which the average nominations among all traits across any one name generator are homophilic. Across all name generators demographic traits showed the most homophily in nominations. See Figs. SA4–SA6 for detailed plots of all traits across all name generators.