Skip to main content

Extracting Interest Tags from Twitter User Biographies

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8870))

Abstract

Twitter, one of the most popular social media platforms, has been studied from different angles. One of the important sources of information in Twitter is users’ biographies, which are short self-introductions written by users in free form. Biographies often describe users’ background and interests. However, to the best of our knowledge, there has not been much work trying to extract information from Twitter biographies. In this work, we study how to extract information revealing users’ personal interests from Twitter biographies. A sequential labeling model is trained with automatically constructed labeled data. The popular patterns expressing user interests are extracted and analyzed. We also study the connection between interest tags extracted from user biographies and tweet content, and find that there is a weak linkage between them, suggesting that biographies can potentially serve as a complimentary source of information to tweets.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Benson, E., Haghighi, A., Barzilay, R.: Event discovery in social media feeds. In: Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1, pp. 389–398. Association for Computational Linguistics, Stroudsburg (2011)

    Google Scholar 

  2. Burger, J.D., Henderson, J., Kim, G., Zarrella, G.: Discriminating gender on Twitter. In: Proceedings of the Conference on Empirical Methods in Natural Language Processing, pp. 1301–1309. Association for Computational Linguistics, Stroudsburg (2011)

    Google Scholar 

  3. Counts, S., Stecher, K.B.: Self-presentation of personality during online profile creation. In: Proceedings of International AAAI Conference on Weblogs and Social Media, pp. 191–194. The AAAI Press, Dublin (2012)

    Google Scholar 

  4. Dong, W., Qiu, M., Zhu, F.: Who am i on Twitter?: A cross-country comparison. In: Proceedings of the Companion Publication of the 23rd International Conference on World Wide Web Companion, pp. 253–254 (2014)

    Google Scholar 

  5. Filippova, K.: User demographics and language in an implicit social network. In: Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning, pp. 1478–1488. Association for Computational Linguistics, Stroudsburg (2012)

    Google Scholar 

  6. Gimpel, K., Schneider, N., O’Connor, B., Das, D., Mills, D., Eisenstein, J., Heilman, M., Yogatama, D., Flanigan, J., Smith, N.A.: Part-of-speech tagging for Twitter: annotation, features, and experiments. In: Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies: Short Papers - Volume 2, pp. 42–47. Association for Computational Linguistics, Stroudsburg (2011)

    Google Scholar 

  7. Hagger-Johnson, G., Egan, V., Stillwell, D.: Are social networking profiles reliable indicators of sensational interests? Journal of Research in Personality 45(1), 71–76 (2011)

    Article  Google Scholar 

  8. Imran, M., Elbassuoni, S., Castillo, C., Diaz, F., Meier, P.: Practical extraction of disaster-relevant information from social media. In: Proceedings of the 22nd International Conference on World Wide Web Companion, pp. 1021–1024. International World Wide Web Conferences Steering Committee, Republic and Canton of Geneva, Switzerland (2013)

    Google Scholar 

  9. Lampe, C.A., Ellison, N., Steinfield, C.: A familiar face(book): Profile elements as signals in an online social network. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 435–444. ACM, New York (2007)

    Chapter  Google Scholar 

  10. Liu, Z., Chen, X., Sun, M.: Mining the interests of Chinese microbloggers via keyword extraction. Frontiers of Computer Science, 76–87 (2012)

    Google Scholar 

  11. Marwick, A.E., et al.: I tweet honestly, I tweet passionately: Twitter users, context collapse, and the imagined audience. New Media & Society 13(1), 114–133 (2011)

    Article  Google Scholar 

  12. Mukherjee, A., Liu, B.: Improving gender classification of blog authors. In: Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing, pp. 207–217. Association for Computational Linguistics, Stroudsburg (2010)

    Google Scholar 

  13. Nguyen, D., Smith, N.A., Rosé, C.P.: Author age prediction from text using linear regression. In: Proceedings of the 5th ACL-HLT Workshop on Language Technology for Cultural Heritage, Social Sciences, and Humanities, pp. 115–123. Association for Computational Linguistics, Stroudsburg (2011)

    Google Scholar 

  14. Nosko, A., Wood, E., Zivcakova, L., Molema, S., De Pasquale, D., Archer, K.: Disclosure and use of privacy settings in Facebook profiles: evaluating the impact of media context and gender. Social Networking, 1–8 (2013)

    Google Scholar 

  15. Pennacchiotti, M., Popescu, A.M.: Democrats, republicans and Starbucks afficionados: user classification in Twitter. In: Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 430–438. ACM, New York (2011)

    Google Scholar 

  16. Qiu, L., Lin, H., Leung, A.K.Y.: Cultural differences and switching of in-group sharing behavior between an American (Facebook) and a Chinese (Renren) social networking site. Journal of Cross-Cultural Psychology 44(1), 106–121 (2013)

    Article  Google Scholar 

  17. Ritter, A., Clark, S., Mausam, Etzioni, O.: Named entity recognition in tweets: an experimental study. In: Proceedings of the Conference on Empirical Methods in Natural Language Processing, pp. 1524–1534. Association for Computational Linguistics, Stroudsburg (2011)

    Google Scholar 

  18. Ritter, A., Mausam, E.O., Clark, S.: Open domain event extraction from Twitter. In: Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 1104–1112. ACM, New York (2012)

    Chapter  Google Scholar 

  19. Rosenthal, S., McKeown, K.: Age prediction in blogs: A study of style, content, and online behavior in pre- and post-social media generations. In: Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, vol. 1, pp. 763–772. Association for Computational Linguistics, Stroudsburg (2011)

    Google Scholar 

  20. Roshchina, A., Cardiff, J., Rosso, P.: User profile construction in the twin personality-based recommender system. In: Proceedings of the Workshop on Sentiment Analysis where AI meets Psychology, pp. 73–79. Asian Federation of Natural Language Processing, Chiang Mai (2011)

    Google Scholar 

  21. Wu, W., Zhang, B., Ostendorf, M.: Automatic generation of personalized annotation tags for twitter users. In: Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics, pp. 689–692. Association for Computational Linguistics, Stroudsburg (2010)

    Google Scholar 

  22. Yang, H., Li, Y.: Identifying user needs from social media. IBM Research report (2013)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this paper

Cite this paper

Ding, Y., Jiang, J. (2014). Extracting Interest Tags from Twitter User Biographies. In: Jaafar, A., et al. Information Retrieval Technology. AIRS 2014. Lecture Notes in Computer Science, vol 8870. Springer, Cham. https://doi.org/10.1007/978-3-319-12844-3_23

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-12844-3_23

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-12843-6

  • Online ISBN: 978-3-319-12844-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics