TY - JOUR AU - Mitzlaff, Folke AU - Atzmueller, Martin AU - Benz, Dominik AU - Hotho, Andreas AU - Stumme, Gerd T1 - User-Relatedness and Community Structure in Social Interaction Networks JO - CoRR/abs PY - 2013/ VL - 1309.3888 IS - SP - EP - UR - M3 - KW - venus KW - itegpub KW - ubiquitous KW - social KW - l3s KW - 2013 KW - myown KW - iteg KW - data KW - mining KW - web L1 - SN - N1 - N1 - AB - ER - TY - GEN AU - Mitzlaff, Folke AU - Atzmueller, Martin AU - Benz, Dominik AU - Hotho, Andreas AU - Stumme, Gerd A2 - T1 - User-Relatedness and Community Structure in Social Interaction Networks JO - PB - AD - PY - 2013/ VL - IS - SP - EP - UR - http://arxiv.org/abs/1309.3888 M3 - KW - itegpub KW - networks KW - evidence KW - social KW - l3s KW - community KW - 2013 KW - myown KW - iteg L1 - N1 - N1 - AB - With social media and the according social and ubiquitous applications
finding their way into everyday life, there is a rapidly growing amount of user
generated content yielding explicit and implicit network structures. We
consider social activities and phenomena as proxies for user relatedness. Such
activities are represented in so-called social interaction networks or evidence
networks, with different degrees of explicitness. We focus on evidence networks
containing relations on users, which are represented by connections between
individual nodes. Explicit interaction networks are then created by specific
user actions, for example, when building a friend network. On the other hand,
more implicit networks capture user traces or evidences of user actions as
observed in Web portals, blogs, resource sharing systems, and many other social
services. These implicit networks can be applied for a broad range of analysis
methods instead of using expensive gold-standard information.
In this paper, we analyze different properties of a set of networks in social
media. We show that there are dependencies and correlations between the
networks. These allow for drawing reciprocal conclusions concerning pairs of
networks, based on the assessment of structural correlations and ranking
interchangeability. Additionally, we show how these inter-network correlations
can be used for assessing the results of structural analysis techniques, e.g.,
community mining methods. ER - TY - CHAP AU - Niebler, Thomas AU - Singer, Philipp AU - Benz, Dominik AU - Körner, Christian AU - Strohmaier, Markus AU - Hotho, Andreas A2 - Serdyukov, Pavel A2 - Braslavski, Pavel A2 - Kuznetsov, SergeiO. A2 - Kamps, Jaap A2 - Rüger, Stefan A2 - Agichtein, Eugene A2 - Segalovich, Ilya A2 - Yilmaz, Emine T1 - How Tagging Pragmatics Influence Tag Sense Discovery in Social Annotation Systems T2 - Advances in Information Retrieval PB - Springer Berlin Heidelberg CY - PY - 2013/ VL - 7814 IS - SP - 86 EP - 97 UR - http://dx.doi.org/10.1007/978-3-642-36973-5_8 M3 - 10.1007/978-3-642-36973-5_8 KW - pragmtics KW - tagging KW - itegpub KW - ecir13 KW - discovery KW - l3s KW - 2013 KW - iteg KW - sense L1 - SN - 978-3-642-36972-8 N1 - N1 - AB - The presence of emergent semantics in social annotation systems has been reported in numerous studies. Two important problems in this context are the induction of semantic relations among tags and the discovery of different senses of a given tag. While a number of approaches for discovering tag senses exist, little is known about which ER -