Homophily and Long-Run Integration in Social Networks

We model network formation when heterogeneous nodes enter sequentially and form connections through both random meetings and network-based search, but with type-dependent biases. We show that there is "long-run integration," whereby the composition of types in sufficiently old nodes' neighborhoods approaches the global type distribution, provided that the network-based search is unbiased. However, younger nodes' connections still reflect the biased meetings process. We derive the type-based degree distributions and group-level homophily patterns when there are two types and location-based biases. Finally, we illustrate aspects of the model with an empirical application to data on citations in physics journals.Comment: 39 pages, 2 figure

Diversity and Popularity in Social Networks

Homophily, the tendency of linked agents to have similar characteristics, is an im- portant feature of social networks. We present a new model of network formation that allows the linking process to depend on individuals types and study the impact of such a bias on the network structure. Our main results fall into three categories: (i) we compare the distributions of intra- and inter-group links in terms of stochastic dominance, (ii) we show how, at the group level, homophily depends on the groups size and the details of the formation process, and (iii) we understand precisely the determinants of local homophily at the individual level. Especially, we ¯nd that popular individuals have more diverse networks. Our results are supported empirically in the AddHealth data looking at networks of social connections between boys and girls.social networks, homophily, AddHealth, diversity, degree distributions

Stochastic network formation and homophily

This is a chapter of the forthcoming Oxford Handbook on the Economics of Networks

Individualization as driving force of clustering phenomena in humans

One of the most intriguing dynamics in biological systems is the emergence of clustering, the self-organization into separated agglomerations of individuals. Several theories have been developed to explain clustering in, for instance, multi-cellular organisms, ant colonies, bee hives, flocks of birds, schools of fish, and animal herds. A persistent puzzle, however, is clustering of opinions in human populations. The puzzle is particularly pressing if opinions vary continuously, such as the degree to which citizens are in favor of or against a vaccination program. Existing opinion formation models suggest that "monoculture" is unavoidable in the long run, unless subsets of the population are perfectly separated from each other. Yet, social diversity is a robust empirical phenomenon, although perfect separation is hardly possible in an increasingly connected world. Considering randomness did not overcome the theoretical shortcomings so far. Small perturbations of individual opinions trigger social influence cascades that inevitably lead to monoculture, while larger noise disrupts opinion clusters and results in rampant individualism without any social structure. Our solution of the puzzle builds on recent empirical research, combining the integrative tendencies of social influence with the disintegrative effects of individualization. A key element of the new computational model is an adaptive kind of noise. We conduct simulation experiments to demonstrate that with this kind of noise, a third phase besides individualism and monoculture becomes possible, characterized by the formation of metastable clusters with diversity between and consensus within clusters. When clusters are small, individualization tendencies are too weak to prohibit a fusion of clusters. When clusters grow too large, however, individualization increases in strength, which promotes their splitting.Comment: 12 pages, 4 figure

Measuring and mitigating behavioural segregation using Call Detail Records

The overwhelming amounts of data we generate in our daily routine and in social networks has been crucial for the understanding of various social and economic factors. The use of this data represents a low-cost alternative source of information in parallel to census data and surveys. Here, we advocate for such an approach to assess and alleviate the segregation of Syrian refugees in Turkey. Using a large dataset of mobile phone records provided by Turkey's largest mobile phone service operator, Türk Telekom, in the frame of the Data 4 Refugees project, we define, analyse and optimise inter-group integration as it relates to the communication patterns of two segregated populations: refugees living in Turkey and the local Turkish population. Our main hypothesis is that making these two communities more similar (in our case, in terms of behaviour) may increase the level of positive exposure between them, due to the well-known sociological principle of homophily. To achieve this, working from the records of call and SMS origins and destinations between and among both populations, we develop an extensible, statistically-solid, and reliable framework to measure the differences between the communication patterns of two groups. In order to show the applicability of our framework, we assess how house mixing strategies, in combination with public and private investment, may help to overcome segregation. We first identify the districts of the Istanbul province where refugees and local population communication patterns differ in order to then utilise our framework to improve the situation. Our results show potential in this regard, as we observe a significant reduction of segregation while limiting, in turn, the consequences in terms of rent increase

Group Inequality

This paper explores conditions under which inequality across social groups can emerge from initially group-egalitarian distributions and persist across generations despite equality of eco- nomic opportunity. These conditions arise from interactions among three factors: the extent of segregation in social networks, the strength of interpersonal spillovers in human capital accumu- lation, and the responsiveness of relative wages to the skill composition in production. Social segregation is critical in generating these results: group inequality cannot emerge or persist un- der conditions of equal opportunity unless segregation su¢ ciently great. We also show that if an initially disadvantaged group is su¢ ciently small, integration above a threshold level can induce both groups to invest more in human capital, while the opposite holds if the disadvantaged group is large.segregation, networks, group inequality, human capital