Gueorgi Kossinets

Effects of missing data in social networks

We perform sensitivity analyses to assess the impact of missing data on the structural properties of social networks. The social network is conceived of as being generated by a bipartite graph, in which actors are linked together via multiple interaction contexts or affiliations. We discuss three principal missing data mechanisms: network boundary specification (non-inclusion of actors or affiliations), survey non-response, and censoring by vertex degree (fixed choice design), examining their impact on the scientific collaboration network from the Los Alamos E-print Archive as well as random bipartite graphs. The simulation results show that network boundary specification and fixed choice designs can dramatically alter estimates of network-level statistics. The observed clustering and assortativity coefficients are overestimated via omission of affiliations or fixed choice thereof, and underestimated via actor non-response, which results in inflated measurement error. We also find that social networks with multiple interaction contexts may have certain interesting properties due to the presence of overlapping cliques. In particular, assortativity by degree does not necessarily improve network robustness to random omission of nodes as predicted by current theory.

Origins of Homophily in an Evolving Social Network

The authors investigate the origins of homophily in a large university community, using network data in which interactions, attributes, and affiliations are all recorded over time. The analysis indicates that highly similar pairs do show greater than average propensity to form new ties; however, it also finds that tie formation is heavily biased by triadic closure and focal closure, which effectively constrain the opportunities among which individuals may select. In the case of triadic closure, moreover, selection to “friend of a friend” status is determined by an analogous combination of individual preference and structural proximity. The authors conclude that the dynamic interplay of choice homophily and induced homophily, compounded over many “generations” of biased selection of similar individuals to structurally proximate positions, can amplify even a modest preference for similar others, via a cumulative advantage–like process, to produce striking patterns of observed homophily.

Mobile health apps: adoption, adherence, and abandonment

A myriad of mobile technologies purport to help individuals change or maintain health-related behaviors, for instance by increasing motivation or self-awareness. We provide a fine-grained categorization of popular mobile health applications and also examine the perceived efficacy of apps along with reasons underlying both app adoption and abandonment. Our findings bear implications for future tools designed to support health management.

Online microsurveys for user experience research

This case study presents a critical analysis of microsurveys as a method for conducting user experience research. We focus specifically on Google Consumer Surveys (GCS) and analyze a combination of log data and GCSs run by the authors to investigate how they are used, who the respondents are, and the quality of the data. We find that such microsurveys can be a great way to quickly and cheaply gather large amounts of survey data, but that there are pitfalls that user experience researchers should be aware of when using the method.

Social networks: looking ahead

By now, online social networks have become an indispensable part of both online and offline lives of human beings. A large fraction of time spent online by a user is directly influence by the social networks to which he/she belongs. This calls for a deeper examination of social networks as large-scale dynamic objects that foster efficient person-person interaction. The goal of our panel is to discuss social networks from various research angles. In particular, we plan to focus on the following broad research-related topics: large scale data mining, algorithmic questions, sociological aspects, privacy, web search, etc. We will also discuss the business and societal impacts of social networks. Each of these topics has generated a lot of research in recent years and while taking stock of what has been done, we will also be discussing the directions in which these topics are headed, from both science and society points of view. Our panel will consist of eminent researchers, who have worked/been working on an eclectic and diverse mix of problems in social networks