Analysis of Social Media and Ubiquitous Data: International by Wolfgang Woerndl, Alexander Manhardt (auth.), Martin

By Wolfgang Woerndl, Alexander Manhardt (auth.), Martin Atzmueller, Andreas Hotho, Markus Strohmaier, Alvin Chin (eds.)

This booklet constitutes the joint completely refereed post-proceedings of The Modeling Social Media Workshop, MSM 2010 held in Toronto, Canada in June 2010 and the foreign Workshop on Mining Ubiquitous and Social Environments, MUSE 2010, held in Barcelona, Spain in September 2010.

The 8 revised complete papers incorporated have been rigorously reviewed and chosen after rounds of reviewing and revision. The papers handle a number of facets of the research and engineering of socio-computational platforms within which social, ubiquitous and computational methods are interdependent and tightly interwoven

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Extra resources for Analysis of Social Media and Ubiquitous Data: International Workshops MSM 2010, Toronto, Canada, June 13, 2010, and MUSE 2010, Barcelona, Spain, September 20, 2010, Revised Selected Papers

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3 Empirical Material The two online discussion groups were selected for two reasons. First I wanted to have two groups of similar sizes in terms of number of people and number of posts. Secondly I wanted to have groups that were different in terms of content since I wanted to find out what a content independent analysis can reveal about a group. Also, though not a member, I happened to be familiar with both groups. (Please note that subject in this text refers to a person in accord with tradition in experimental psychology) The two data sets consisted of 1604 and 971 posts respectively.

Now, if one morning the ringer is not reactivated an outlier can be detected by the system and the question arises whether the user should be notified so he or she doesn’t miss any incoming calls. 6 Conclusion and Outlook The goal of this work is a unified approach for collecting data about user actions on mobile devices in granularity appropriate for user modeling. To realize this first step of the user modeling process, we have designed and implemented a framework for mobile user activity logging on Windows Mobile PDAs based on the MyExperience project.

Zhang and Tanniru made an agent based study where the characteristics included expertise level, activeness level, sharing level and social gain. In this study it was assumed that the quantity and quality of the messages posted was an indicator of social status (reputation) [5]. Another indicator of status that has been used is the number of in-links to a person. Agarwal et al developed a model for identifying the most influential bloggers in community blogs. In their model, a weighted measure combined by number of comments, number of in- and out-links and length of the post was used as an indicator of social status (influence).

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