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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 references23

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            Diurnal and seasonal mood vary with work, sleep, and daylength across diverse cultures.

            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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              Group formation in large social networks

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                Author and article information

                Journal
                2014-02-07
                Article
                10.1109/TSMC.2014.2378215
                1402.1778
                4e9390b3-64c9-4195-8880-a514aee6b733

                http://arxiv.org/licenses/nonexclusive-distrib/1.0/

                History
                Custom metadata
                IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol.45, no.4, pp.559,570, April 2015
                12 pages, 9 figures - Transactions on Systems, Man and Cybernetics: Systems - under review
                cs.SI cs.CY physics.data-an physics.soc-ph

                Social & Information networks,General physics,Applied computer science,Mathematical & Computational physics

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