Why we twitter: understanding microblogging usage and communities
Proceedings of the 9th WebKDD and 1st SNA-KDD 2007 workshop on Web mining and social network analysis
Proceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
An empirical study on learning to rank of tweets
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics
Ranking Approaches for Microblog Search
WI-IAT '10 Proceedings of the 2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 01
#TwitterSearch: a comparison of microblog search and web search
Proceedings of the fourth ACM international conference on Web search and data mining
TI: an efficient indexing mechanism for real-time search on tweets
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
RAProp: ranking tweets by exploiting the tweet/user/web ecosystem and inter-tweet agreement
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
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This paper interests in social search over social networking services, typically in microblogging networks. We propose a new approach that integrates, within a Bayesian network model, new relevance factors such as the social importance of microbloggers and the temporal magnitude of tweets. In particular, the social importance of a microblogger is assimilated to his influence on the social network. This property is evaluated by applying PageRank algorithm on the social network of retweets and mentions. The temporal magnitude of microblogs is estimated based on temporal neighbors that present similar query terms. To validate our approach, we conducted a series of experiments on the TREC 2011 Microblog dataset. Results show that the integration of social and temporal features increases the retrieval effectiveness.