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Sunbelt XXXI International Network for Social Network ... - INSNA

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Structure And Consistency: Assessment Of <strong>Social</strong> Bookmarking CommunitiesMitzlaff, Folke; Atzmueller, Martin; Benz, Dominik; Hotho, Andreas; Stumme, GerdOnline <strong>Social</strong> <strong>Network</strong>sCommunity Detection, Evaluation, Folksonomies, Online <strong>Network</strong>sTHURS.PM1The growing amount of user generated content in the “Web 2.0” entails an increasing need <strong>for</strong> personalized access to the wealth of in<strong>for</strong>mation available inorder to prevent the user from getting “lost in data”. Community detection and user recommendation techniques, <strong>for</strong> example, allow <strong>for</strong> presenting onlycontent which was provided by “relevant” users. But how to judge whether a group of users <strong>for</strong>ms a relevant community is still dif&#64257;cult, withoutapplying gold‐standard data which is rarely available. Focussing on the evaluation of user communities, this paper provides the basis <strong>for</strong> an appropriateevaluation framework. It tackles the problem by analyzing so‐called evidence networks that encompass evidences <strong>for</strong> user relationships in social bookmarkingsystems. Our findings suggest that these networks exhibit common community structure. Furthermore, standard evaluation metrics are applied <strong>for</strong> assessingthe contained community structure, giving new insights concerning the networks as well as the metrics. The provided results motivate an approach <strong>for</strong>assessing communities using such networks.Structures Of Collaboration Among Movie TechniciansVernet, AntoineCollaboration, coordination and cooperationCulture, Collaboration, Large‐scale <strong>Network</strong>s, TeamSAT.AM2The aims of this study is to better understand the process of reproduction of work teams over time. The study describes relationships between the core teamof technicians (cinematographer, editor, set designer, costume designer), producers and directors. It aims at understanding the influence of recurringcollaborations on career outcomes. Using descriptive statistics on large networks and extraction of subnetworks from this network of collaboration (using thein<strong>for</strong>mation collected during an extensive qualitative research on the careers of movie technicians conducted in France and the US <strong>for</strong> my PhD, to assure thatthe subnetworks are meaningful) we study how careers unfold in time and how enduring work teams are constituted. This allows us to investigate the impactof recurring relationships on the duration of one's career and on one's success.

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