Contextual Synchronization for Efficient Social Collaborations: A Case Study on TweetPulse

Conference paper
Part of the Studies in Computational Intelligence book series (SCI, volume 446)

Abstract

It is important to be aware of user contexts for supporting efficient collaborations among them. The goal of this paper is to present a social collaboration platform where we can understand i) how the user contexts are dynamically changing over time, and ii) how the user contexts are mixed with multiple sub-contexts together. Thereby, we have implemented TweetPulse, which is a a Twitter-based tool for context monitoring and propagation system in a given social network. TweetPulse can match contexts of the users (and integrate them) to find the most relevant users. Eventually, collaboration among users are contextually synchronized. by dynamically organizing a number of communities. A set of users in each community come together to share skills or core competencies and resources at the moment. We have shown the experimental results collected from a collaborative information searching system in terms of i) setting thresholds, ii) searching performance, and iii) scalability testing.

Keywords

Semantic Distance Name Entity Recognition Collaborative Network User Context Group Context 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Department of Computer EngineeringYeungnam UniversityGyeongsanKorea

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