Skip to main content

A Sentiment Analysis of Audiences on Twitter: Who Is the Positive or Negative Audience of Popular Twitterers?

  • Conference paper
Convergence and Hybrid Information Technology (ICHIT 2011)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 6935))

Included in the following conference series:

Abstract

Microblogging is a new informal communication medium of blogging that differs from a traditional blog in which content is much shorter. Microbloggers post about topics that describe their current status. Twitter is a popular microblogging service and social media where users read and write millions of short messages on any topics within the 140-character limit. Twitter is used to find the context of social trend. Popular or influential users tweet about their status and are retweeted, mentioned or replied to by their audience. A sentiment analysis of the tweets of popular users and their audiences discovers whether the audience is favorable or unfavorable to the views expressed by such popular users. We conducted a content analysis of over 1,000,000 tweets mentioning or replying to their thirteen most influential users to discover the sentiment of the audience. Arguably, Twitter messages reflect the silent landscape of sentiment towards its most popular users. This study uses the technique of Sentiment Analysis to deliver a valid popularity indicator or measure.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
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

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Cha, M., Haddadi, H., Benevenuto, F., Gummadi, K.P.: Measuring user influence in Twitter: The million follower fallacy. In: Proceedings of the 4th International AAAI Conference on Weblogs and Social Media (ICWSM), Washington DC (2010)

    Google Scholar 

  2. Honeycutt, C., Herring, S.C.: Beyond Microblogging: Conversation and Collaboration via Twitter. In: 42nd Hawaii International Conference on System Sciences, Hawaii, pp. 1–10 (2009)

    Google Scholar 

  3. Huberman, B.A., Romero, D.M., Wu, F.: Social networks that matter: Twitter Under the Microscope. First Monday 14(1) (2009)

    Google Scholar 

  4. Jansen, B.J., Zhang, M., Sobel, K., Chowdury, A.: Twitter power: Tweets as electronic word of mouth. Journal of the American Society for Information Science and Technology 60(11), 2169–2188 (2009)

    Article  Google Scholar 

  5. Java, A., Song, X., Finin, T., Tseng, B.: Why we Twitter: understanding microblogging usage and communities. In: Proceedings of 9th WebKDD and 1st SNA-KDD Workshop on Web Mining and Social Network Analysis, pp. 56–65. ACM, San Jose (2007)

    Google Scholar 

  6. Kwak, H., Lee, C., Park, H., Moon, S.: What is Twitter, a social network or a news media? In: Proceedings of the 19th International Conference on World Wide Web, pp. 591–600. ACM, Raleigh (2010)

    Google Scholar 

  7. Pennebaker, J.W., Francis, M.E., Booth, R.J.: Linguistic inquiry and word count: LIWC, Computer software. Erlbaum, Mahwah (2001)

    Google Scholar 

  8. Pennebaker, J.W., Chung, C.K., Ireland, M., Gonzales, A., Booth, R.J.: The development and psychometric properties. In: LIWC 2007, Austin, TX, LIWC. Net (2007)

    Google Scholar 

  9. Romero, D.M., Galuba, W., Asur, S., Huberman, B.A.: Influence and passivity in social media, pp. 113–114. ACM, New York (2011)

    Google Scholar 

  10. Tausczik, Y.R., Pennebaker, J.W.: The psychological meaning of words: LIWC and computerized text analysis methods. Journal of Language and Social Psychology 29(1) (2010)

    Google Scholar 

  11. Thelwall, M., Buckley, K., Paltoglou, G.: Sentiment in Twitter events. Journal of the American Society for Information Science and Technology (2011)

    Google Scholar 

  12. Tumasjan, A., Sprenger, T.O., Sandner, P.G., Welpe, I.M.: Predicting elections with Twitter: What 140 characters reveal about political sentiment. In: 4th International AAAI Conference on Weblogs and Social Media, ICWSM (2010)

    Google Scholar 

  13. Weng, J., Lim, E.P., Jiang, J., He, Q.: TwitterRank: Finding topic-sensitive influential twitterers. In: Proceedings of the Third ACM International Conference on Web Search and Data Mining, pp. 261–270. ACM, New York (2010)

    Chapter  Google Scholar 

  14. Yu, B., Kaufmann, S., Diermeier, D.: Exploring the characteristics of opinion expressions for political opinion classification. In: Proceedings of the 2008 International Conference on Digital Government Research, Montreal, pp. 82–91 (2008)

    Google Scholar 

  15. Zhang, X., Fuehres, H., Gloor, P.: Predicting stock market indicators through Twitter-“I hope it is not as bad as I fear”. In: COIN Collaborative Innovations Networks Conference, pp. 1–8. Elsevier, Amsterdam (2010)

    Google Scholar 

  16. Bollen, J., Mao, H., Zeng, X.: Twitter mood predicts the stock market. Journal of Computational Science 2(1), 1–8 (2011)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2011 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Bae, Y., Lee, H. (2011). A Sentiment Analysis of Audiences on Twitter: Who Is the Positive or Negative Audience of Popular Twitterers?. In: Lee, G., Howard, D., Ślęzak, D. (eds) Convergence and Hybrid Information Technology. ICHIT 2011. Lecture Notes in Computer Science, vol 6935. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24082-9_89

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-24082-9_89

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-24081-2

  • Online ISBN: 978-3-642-24082-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics