A Weighted Multi-factor Algorithm for Microblog Search

  • Lulin Zhao
  • Yi Zeng
  • Ning Zhong
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6890)


As a fast and social information communication media, microblog, especially Twitter, has gained increasing popularity in recent years. Given the fact that a great volume of new tweets are being generated every second, ranking them to find the most relevant information is a challenging matter. The short length of tweets makes direct adoptions of traditional information retrieval algorithms to microblog search very hard. In this paper, we focus on the ranking strategies of microblogs, six factors are summarized to measure a user’s social influence, and each of them are highly relevant to the social network properties of the microblog authors and the properties of the microblog itself. Based on these factors, several ranking measures for Twitter search are examined. As a step forward, we propose a weighted multi-factor ranking algorithm (WMFR). By using a public Twitter search dataset, through Kendall’s τ correlation analysis on user selection and algorithm selection of tweets, we conclude that the proposed WMFR algorithm is more effective compared to several existing algorithms.


Social Influence Weighted Coefficient Short Message Service Rank List Ranking Algorithm 
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 2011

Authors and Affiliations

  • Lulin Zhao
    • 1
  • Yi Zeng
    • 1
  • Ning Zhong
    • 1
    • 2
  1. 1.International WIC InstituteBeijing University of TechnologyBeijingChina
  2. 2.Department of Life Science and InformaticsMaebashi Institute of TechnologyMaebashi-CityJapan

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