TY - CONF AU - Zoller, Daniel AU - Doerfel, Stephan AU - Jäschke, Robert AU - Stumme, Gerd AU - Hotho, Andreas A2 - T1 - On Publication Usage in a Social Bookmarking System T2 - Proceedings of the 2015 ACM Conference on Web Science PB - CY - PY - 2015/ M2 - VL - IS - SP - EP - UR - M3 - KW - 2015 KW - altmetrics KW - bookmarking KW - impact KW - myown KW - publication KW - social KW - usage L1 - SN - N1 - N1 - AB - Scholarly success is traditionally measured in terms of citations to publications. With the advent of publication man- agement and digital libraries on the web, scholarly usage data has become a target of investigation and new impact metrics computed on such usage data have been proposed – so called altmetrics. In scholarly social bookmarking sys- tems, scientists collect and manage publication meta data and thus reveal their interest in these publications. In this work, we investigate connections between usage metrics and citations, and find posts, exports, and page views of publications to be correlated to citations. ER - TY - GEN AU - A2 - Jannach, Dietmar A2 - Freyne, Jill A2 - Geyer, Werner A2 - Guy, Ido A2 - Hotho, Andreas A2 - Mobasher, Bamshad T1 - Proceedings of the 6th Workshop on Recommender Systems and the Social

Web (RSWeb 2014) co-located with the 8th ACM Conference on Recommender

Systems (RecSys 2014), Foster City, CA, USA, October 6, 2014 JO - PB - CEUR-WS.org AD - PY - 2014/ VL - 1271 IS - SP - EP - UR - http://ceur-ws.org/Vol-1271 M3 - KW - 2014 KW - myown KW - proceedings KW - recommender KW - social KW - workshop L1 - N1 - N1 - AB - ER - TY - JOUR AU - Mitzlaff, Folke AU - Atzmueller, Martin AU - Hotho, Andreas AU - Stumme, Gerd T1 - The social distributional hypothesis: a pragmatic proxy for homophily in online social networks JO - Social Network Analysis and Mining PY - 2014/ VL - 4 IS - 1 SP - EP - UR - http://dx.doi.org/10.1007/s13278-014-0216-2 M3 - 10.1007/s13278-014-0216-2 KW - 2014 KW - distributional KW - hypothesis KW - myown KW - pragmatic KW - proxy KW - social L1 - SN - N1 - The social distributional hypothesis: a pragmatic proxy for homophily in online social networks - Springer N1 - AB - Applications of the Social Web are ubiquitous and have become an integral part of everyday life: Users make friends, for example, with the help of online social networks, share thoughts via Twitter, or collaboratively write articles in Wikipedia. All such interactions leave digital traces; thus, users participate in the creation of heterogeneous, distributed, collaborative data collections. In linguistics, the ER - TY - GEN AU - Singer, Philipp AU - Helic, Denis AU - Hotho, Andreas AU - Strohmaier, Markus A2 - T1 - HypTrails: A Bayesian Approach for Comparing Hypotheses about Human

Trails on the Web JO - PB - AD - PY - 2014/ VL - IS - SP - EP - UR - http://arxiv.org/abs/1411.2844 M3 - KW - 2014 KW - bayesian KW - comparing KW - hypotheses KW - myown KW - semantic KW - social L1 - N1 - HypTrails: A Bayesian Approach for Comparing Hypotheses about Human

Trails N1 - AB - When users interact with the Web today, they leave sequential digital trails

on a massive scale. Examples of such human trails include Web navigation,

sequences of online restaurant reviews, or online music play lists.

Understanding the factors that drive the production of these trails can be

useful for e.g., improving underlying network structures, predicting user

clicks or enhancing recommendations. In this work, we present a general

approach called HypTrails for comparing a set of hypotheses about human trails

on the Web, where hypotheses represent beliefs about transitions between

states. Our approach utilizes Markov chain models with Bayesian inference. The

main idea is to incorporate hypotheses as informative Dirichlet priors and to

leverage the sensitivity of Bayes factors on the prior for comparing hypotheses

with each other. For eliciting Dirichlet priors from hypotheses, we present an

adaption of the so-called (trial) roulette method. We demonstrate the general

mechanics and applicability of HypTrails by performing experiments with (i)

synthetic trails for which we control the mechanisms that have produced them

and (ii) empirical trails stemming from different domains including website

navigation, business reviews and online music played. Our work expands the

repertoire of methods available for studying human trails on the Web. ER - TY - JOUR AU - Strohmaier, Markus AU - Wagner, Claudia T1 - Computational Social Science for the World Wide Web JO - Intelligent Systems PY - 2014/ VL - IS - SP - 84 EP - 88 UR - M3 - KW - computational KW - social L1 - SN - N1 - N1 - AB - ER -