Contextual Synchronization for Efficient Social Collaborations: A Case Study on TweetPulse
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.
KeywordsSemantic Distance Name Entity Recognition Collaborative Network User Context Group Context
Unable to display preview. Download preview PDF.
- 1.Berger, A.L., Pietra, S.D., Pietra, V.J.D.: A maximum entropy approach to natural language processing. Computational Linguistics 22(1), 39–71 (1996)Google Scholar
- 4.Jung, J.J.: Collaborative web browsing based on semantic extraction of user interests with bookmarks. Journal of Universal Computer Science 11(2), 213–228 (2005)Google Scholar
- 5.Jung, J.J.: Visualizing recommendation flow on social networks. Journal of Universal Computer Science 11(11), 1780–1791 (2005)Google Scholar