The anatomy of a large-scale hypertextual Web search engine
WWW7 Proceedings of the seventh international conference on World Wide Web 7
Extracting reputation in multi agent systems by means of social network topology
Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 1
TwitterRank: finding topic-sensitive influential twitterers
Proceedings of the third ACM international conference on Web search and data mining
Tweet, Tweet, Retweet: Conversational Aspects of Retweeting on Twitter
HICSS '10 Proceedings of the 2010 43rd Hawaii International Conference on System Sciences
Characterizing debate performance via aggregated twitter sentiment
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Time is of the essence: improving recency ranking using Twitter data
Proceedings of the 19th international conference on World wide web
What is Twitter, a social network or a news media?
Proceedings of the 19th international conference on World wide web
Automatic generation of personalized annotation tags for Twitter users
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for 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
Little search game: term network acquisition via a human computation game
Proceedings of the 22nd ACM conference on Hypertext and hypermedia
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In order to compute page rankings, search algorithms primarily utilize information related to page content and link structure. Microblog as a phenomenon of today provides additional, potentially relevant, information --- short messages often containing hypertext links to web resources. Such source is particularly valuable when considering a temporal aspect of information, which is being published every second. In this paper we present a method for resource ranking based on Twitter data structure processing. We apply various graph algorithms leveraging the notion of a node centrality in order to deduce microblog-based resource ranking. Our method ranks a microblog user based on his followers count with respect to a number of (re)posts and reflects it into resource ranking. The evaluation of the method showed that micro-based resource ranking a ) can not be substituted by a common form of an explicit user rating, and b ) has the great potential for search improvement.