Center of Attention: How Facebook Users Allocate Attention across Friends

By Lars Backstrom, Eytan Bakshy, Jon M. Kleinberg, Thomas M. Lento, Itamar Rosenn. 2011

96 citations recorded by the source corpus.

An individual's personal network — their set of social contacts — is a basic object of study in sociology. Studies of personal networks have focused on their size (the number of contacts) and their composition (in terms of categories such as kin and co-workers). Here we propose a new measure for the analysis of personal networks, based on the way in which an individual divides his or her attention across contacts. This allows us to contrast people who focus a large fraction of their interactions on a small set of close friends with people who disperse their attention more widely. Using data from Facebook, we find that this balance of attention is a relatively stable property of an individual over time, and that it displays interesting variation across both different groups of people and different modes of interaction. In particular, activities based on communication involve a much higher focus of attention than activities based simply on observation, and these two types of modalities also exhibit different forms of variation in interaction patterns both within and across groups. Finally, we contrast the amount of attention paid by individuals to their most frequent contacts with the rate of change in the identities of these contacts, providing a measure of churn for this set.

Subfields: Sociology and Political Science, Statistical and Nonlinear Physics

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Citations in the corpus

Social Data: Biases, Methodological Pitfalls, and Ethical Boundaries (2019, background): “Backstrom et al. (2011) found diﬀerences in how users balance their attention within their social network, with some users being more focused than others depending on their demographics (e.g., women tend to be more focused toward their top friends); while others indicate that how users interact…”
Quantifying the invisible audience in social networks (2013, background): “In addition, there are consistent patterns in online communities that might bias estimates: for example, the prevalence of lurkers who do not provide feedback or contribute [29] and a typical pattern of focusing interactions on a small number of people in the network [4].”
Quantifying Information Overload in Social Media and Its Impact on Social Contagions (2014, background): “The work most closely related ours (Backstrom et al. 2011; Hodas and Lerman 2012; Miritello et al. 2013) investigates the impact that the amount of social ties of a social media user has on the way she interacts or exchanges information with her friends, followees or contacts.”