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      Analysis of a heterogeneous social network of humans and cultural objects

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          Abstract

          Modern online social platforms enable their members to be involved in a broad range of activities like getting friends, joining groups, posting/commenting resources and so on. In this paper we investigate whether a correlation emerges across the different activities a user can take part in. To perform our analysis we focused on aNobii, a social platform with a world-wide user base of book readers, who like to post their readings, give ratings, review books and discuss them with friends and fellow readers. aNobii presents a heterogeneous structure: i) part social network, with user-to-user interactions, ii) part interest network, with the management of book collections, and iii) part folksonomy, with books that are tagged by the users. We analyzed a complete and anonymized snapshot of aNobii and we focused on three specific activities a user can perform, namely her tagging behavior, her tendency to join groups and her aptitude to compile a wishlist reporting the books she is planning to read. In this way each user is associated with a tag-based, a group-based and a wishlist-based profile. Experimental analysis carried out by means of Information Theory tools like entropy and mutual information suggests that tag-based and group-based profiles are in general more informative than wishlist-based ones. Furthermore, we discover that the degree of correlation between the three profiles associated with the same user tend to be small. Hence, user profiling cannot be reduced to considering just any one type of user activity (although important) but it is crucial to incorporate multiple dimensions to effectively describe users preferences and behavior.

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          Most cited references 25

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          A new status index derived from sociometric analysis

           Leo Katz (1953)
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            Diurnal and seasonal mood vary with work, sleep, and daylength across diverse cultures.

             S Golder,  M Macy (2011)
            We identified individual-level diurnal and seasonal mood rhythms in cultures across the globe, using data from millions of public Twitter messages. We found that individuals awaken in a good mood that deteriorates as the day progresses--which is consistent with the effects of sleep and circadian rhythm--and that seasonal change in baseline positive affect varies with change in daylength. People are happier on weekends, but the morning peak in positive affect is delayed by 2 hours, which suggests that people awaken later on weekends.
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              Homophily and Contagion Are Generically Confounded in Observational Social Network Studies

              We consider processes on social networks that can potentially involve three factors: homophily, or the formation of social ties due to matching individual traits; social contagion, also known as social influence; and the causal effect of an individual's covariates on their behavior or other measurable responses. We show that, generically, all of these are confounded with each other. Distinguishing them from one another requires strong assumptions on the parametrization of the social process or on the adequacy of the covariates used (or both). In particular we demonstrate, with simple examples, that asymmetries in regression coefficients cannot identify causal effects, and that very simple models of imitation (a form of social contagion) can produce substantial correlations between an individual's enduring traits and their choices, even when there is no intrinsic affinity between them. We also suggest some possible constructive responses to these results.
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                Author and article information

                Journal
                1402.1778

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