A Survey of Recommender Systems in Twitter

  • Su Mon Kywe
  • Ee-Peng Lim
  • Feida Zhu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7710)


Twitter is a social information network where short messages or tweets are shared among a large number of users through a very simple messaging mechanism. With a population of more than 100M users generating more than 300M tweets each day, Twitter users can be easily overwhelmed by the massive amount of information available and the huge number of people they can interact with. To overcome the above information overload problem, recommender systems can be introduced to help users make the appropriate selection. Researchers have began to study recommendation problems in Twitter but their works usually address individual recommendation tasks. There is so far no comprehensive survey for the realm of recommendation in Twitter to categorize the existing works as well as to identify areas that need to be further studied. The paper therefore aims to fill this gap by introducing a taxonomy of recommendation tasks in Twitter, and to use the taxonomy to describe the relevant works in recent years. The paper further presents the datasets and techniques used in these works. Finally, it proposes a few research directions for recommendation tasks in Twitter.


Twitter recommender systems personalization 


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  1. 1.
    Armentano, M.G., Godoy, D.L., Amandi, A.A.: Recommending Information Sources to Information Seekers in Twitter. In: International Workshop on Social Web MiningGoogle Scholar
  2. 2.
    Armentano, M.G., Godoy, D.L., Amandi, A.A.: Towards a Followee Recommender System for Information Seeking Users in Twitter. In: The 2nd International Workshop on Semantic Adaptive Social WebGoogle Scholar
  3. 3.
    Armentano, M.G., Godoy, D.L., Amandi, A.A.: A Topology-Based Approach for Followees Recommendation in Twitter. In: 9th Workshop on Intelligent Techniques for Web Personalization and Recommender Systems, Barcelona, Spain (July 2011)Google Scholar
  4. 4.
    Chen, J., Nairn, R., Nelson, L., Bernstein, M., Chi, E.: Short and Tweet: Experiments on Recommending Content from Information Streams. In: The 28th International Conference on Human Factors in Computing Systems (2010)Google Scholar
  5. 5.
    Choudhary, A., Hendrix, W., Lee, K., Palsetia, D., Liao, W.K.: Social media evolution of the Egyptian revolution. Communications of ACM 55(5), 74–80 (2012)CrossRefGoogle Scholar
  6. 6.
    De Francisci Morales, G., Gionis, A., Lucchese, C.: From Chatter to Headlines: Harnessing the Real-Time Web for Personalized News Recommendation. In: The 5th ACM International Conference on Web Search and Data Mining (2012)Google Scholar
  7. 7.
    Garcia, R., Amatriain, X.: Weighted Content Based Methods for Recommending Connections in Online Social Networks. In: The 2nd ACM Workshop on Recommendation Systems and the Social Web, Barcelona, Spain (June 2010)Google Scholar
  8. 8.
    Golder, S.A., Marwick, A., Yardi, S., Boyd, D.: A structural approach to contact recommendations in online social networks. In: Workshop on Search in Social Media, In conjunction with ACM SIGIR Conference on Information RetrievalGoogle Scholar
  9. 9.
    Hannon, J., Bennett, M., Smyth, B.: Recommending Twitter Users to Follow Using Content and Collaborative Filtering Approaches. In: The 4th ACM Conference on Recommender Systems (2010)Google Scholar
  10. 10.
    Hannon, J., McCarthy, K., Smyth, B.: Finding Useful Users on Twitter: Twittomender the Followee Recommender. In: The 33rd European Conference on Advances in Information Retrieval (2011)Google Scholar
  11. 11.
    Hannon, J., McCarthy, K., Smyth, B.: The Pursuit of Happiness: Searching for Worthy Followees on Twitter. In: The 22nd Irish Conference on Artificial Intelligence and Cognitive Science (August 2011)Google Scholar
  12. 12.
    Huang, J., Thornton, K.M., Efthimiadis, E.N.: Conversational Tagging in Twitter. In: The 21st ACM Conference on Hypertext and Hypermedia, pp. 173–178 (2010)Google Scholar
  13. 13.
    Java, A., Song, X., Finin, T., Tseng, B.: Why We Twitter: Understanding Microblogging Usage and Communities. In: The 9th WebKDD and 1st SNA-KDD 2007 Workshop on Web Mining and Social Network Analysis, pp. 56–65 (2007)Google Scholar
  14. 14.
    Krutkam, W., Saikeaw, K., Chaosakul, A.: Twitter Accounts Recommendation Based on Followers and Lists. In: 3rd Joint International Information and Communication Technology (2010)Google Scholar
  15. 15.
    Kwak, H., Lee, C., Park, H., Moon, S.: What is Twitter, a social network or a news media? In: The 19th International Conference on World Wide Web (2010)Google Scholar
  16. 16.
    Li, T., Yu Wu, Y.Z.: Twitter hash tag prediction algorithm. In: World Congress in Computer Science, Computer Engineering, and Applied Computing (2011)Google Scholar
  17. 17.
    Mazzia, A., Juett, J.: Suggesting hashtags on twitter. EECS 545 (Machine Learning) Couse Project Report,
  18. 18.
    McPherson, M., Smith-Lovin, L., Cook, J.M.: Birds of a Feather: Homophily in Social Networks.Google Scholar
  19. 19.
    Nasirifard, P., Hayes, C.: Tadvise: A Twitter Assistant Based on Twitter Lists. In: Datta, A., Shulman, S., Zheng, B., Lin, S.-D., Sun, A., Lim, E.-P. (eds.) SocInfo 2011. LNCS, vol. 6984, pp. 153–160. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  20. 20.
    Paranjpe, D.: Learning Document Aboutness from Implicit User Feedback and Document Structure. In: ACM Conference on Information and Knowledge Management (2009)Google Scholar
  21. 21.
    Ricci, F., Rokach, L., Shapira, B. (eds.): Recommender Systems Handbook. Springer (2011)Google Scholar
  22. 22.
    Salton, G., Buckley, C.: Term-Weighting Approaches in Automatic Text Retrieval. Information Processing and Management 24(5), 513–523 (1988)CrossRefGoogle Scholar
  23. 23.
    Schafer, J.B., Konstan, J.A., Riedl, J.: E-Commerce Recommendation Applications. Data Mining and Knowledge Discovery 5(1-2), 115–153 (2001)zbMATHCrossRefGoogle Scholar
  24. 24.
    Uysal, I., Croft, B.W.: User Oriented Tweet Ranking: a Filtering Approach to Microblogs. In: The 20th ACM International Conference on Information and Knowledge Management (2011)Google Scholar
  25. 25.
    Zangerle, E., Gassler, W.: Recommending #-Tags in Twitter. In: Workshop on Semantic Adaptive Social Web 2011, in connection with the 19th International Conference on User Modeling, Adaptation and Personalization (2011)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Su Mon Kywe
    • 1
  • Ee-Peng Lim
    • 1
  • Feida Zhu
    • 1
  1. 1.Singapore Management UniversitySingapore

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