Hashtag Popularity on Twitter: Analyzing Co-occurrence of Multiple Hashtags

  • Nargis Pervin
  • Tuan Quang Phan
  • Anindya Datta
  • Hideaki Takeda
  • Fujio Toriumi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9182)

Abstract

Hashtags increase the reachability of a tweet to manifolds and consequently, has the potential to create a wider market for brands. The frequent use of a hashtag features it in the Twitter trending list. In this study we want to understand what contributes to the popularity of a hashtag. Further, hashtags generally come in groups in a tweet. In fact, an investigation on a real world dataset of Great Eastern Japan Earthquake reveals that 50 % of hashtags appear in a tweet with at least another hashtag. How this co-occurrence of hashtags affects its popularity is also not addressed heretofore, which is the focus herein. Results indicate that if a hashtag appears with one or more other similar hashtags, popularity of the hashtag increases. In contrast, if a hashtag appears with dissimilar hashtags, popularity of the focal hashtag decreases. The results reverse when dissimilar hashtags come along with a URL.

Keywords

Twitter Hashtag Hashtag co-occurrence Metacognitive experience 

References

  1. 1.
    Aral, S., Muchnik, L., Sundararajan, A.: Distinguishing influence-based contagion from homophily-driven diffusion in dynamic networks. Proc. Nat. Acad. Sci. 106(51), 21544–21549 (2009)CrossRefGoogle Scholar
  2. 2.
    Berger, J., Milkman, K.L.: What makes online content viral? J. Mark. Res. 49(2), 192–205 (2012)CrossRefGoogle Scholar
  3. 3.
    Berger, J., Milkman, K.: Social transmission, emotion, and the virality of online content. Wharton research paper (2010)Google Scholar
  4. 4.
    Boyd, D., Golder, S., Lotan, G.: Tweet, tweet, retweet: conversational aspects of retweeting on twitter. In: Proceedings of the 2010 43rd Hawaii International Conference on System Sciences, HICSS 2010, pp. 1–10. IEEE Computer Society, Washington, DC, USA (2010)Google Scholar
  5. 5.
    Cohen, J., Cohen, P., West, S., Aiken, L.: Applied Multiple Regression/Correlation Analysis for the Social Sciences. L. Erlbaum Associates, Hillsdale (1983)Google Scholar
  6. 6.
    Cooper, S.: Big mistake: making fun of hashtags instead of using them. October 2013. http://www.forbes.com/sites/stevecooper/2013/10/17/big-mistake-making-fun-of-hashtags-instead-of-using-them/. Accessed 2nd August 2014
  7. 7.
    Doctor, V.: What’s the point of all these hashtags? December 2012. http://www.hashtags.org/platforms/twitter/whats-the-point-of-all-these-hashtags/. Accessed 2nd August 2014
  8. 8.
    Hathaway, J.: Now you can get a \({\$}\)3,000 “social media concierge” for your wedding, March 2014Google Scholar
  9. 9.
    Hughes, A., Palen, L.: Twitter adoption and use in mass convergence and emergency events. Int. J. Emerg. Manage. 6(3), 248–260 (2009)CrossRefGoogle Scholar
  10. 10.
    Ma, Z., Sun, A., Cong, G.: On predicting the popularity of newly emerging hashtags in twitter. J. Am. Soc. Inf. Sci. Technol. 64(7), 1399–1410 (2013)CrossRefGoogle Scholar
  11. 11.
    Pocheptsova, A., Labroo, A.A., Dhar, R.: Making products feel special: when metacognitive difficulty enhances evaluation. J. Mark. Res. 47(6), 1059–1069 (2010)CrossRefGoogle Scholar
  12. 12.
    Reber, R., Schwarz, N.: Effects of perceptual fluency on judgments of truth. Conscious. Cogn. 8(3), 338–342 (1999)CrossRefGoogle Scholar
  13. 13.
    Reber, R., Winkielman, P., Schwarz, N.: Effects of perceptual fluency on affective judgments. Psychol. Sci. 9(1), 45–48 (1998)CrossRefGoogle Scholar
  14. 14.
    Schwarz, N.: Metacognitive experiences in consumer judgment and decision making. J. Consum. Psychol. 14(4), 332–348 (2004)CrossRefGoogle Scholar
  15. 15.
    Shirley, T.: Why hashtags are so important. August 2014. http://www.thelasthurdle.co.uk/hashtags-important/. Accessed 2nd August 2014
  16. 16.
    Song, H., Schwarz, N.: If it’s hard to read, it’s hard to do processing fluency affects effort prediction and motivation. Psychol. Sci. 19(10), 986–988 (2008)CrossRefGoogle Scholar
  17. 17.
    Song, H., Schwarz, N.: If it’s difficult to pronounce, it must be risky fluency, familiarity, and risk perception. Psychol. Sci. 20(2), 135–138 (2009)CrossRefGoogle Scholar
  18. 18.
    Suh, B., Hong, L., Pirolli, P., Chi, E.H.: Want to be retweeted? large scale analytics on factors impacting retweet in twitter network. In: Proceedings of the 2010 IEEE Second International Conference on Social Computing, SOCIALCOM 2010, pp. 177–184. IEEE Computer Society, Washington, DC, USA (2010)Google Scholar
  19. 19.
    Sweeney, D.: Can you legally own a twitter hashtag? March 2012. http://www.socialmediatoday.com/content/can-you-legally-own-twitter-hashtag. Accessed 2nd August 2014
  20. 20.
    Toriumi, F., Sakaki, T., Shinoda, K., Kazama, K., Kurihara, S., Noda, I.: Information sharing on twitter during the 2011 catastrophic earthquake. In: Proceedings of the 22nd International Conference on World Wide Web companion, WWW 2013 Companion, pp. 1025–1028. International World Wide Web Conferences Steering Committee, Republic and Canton of Geneva, Switzerland (2013)Google Scholar
  21. 21.
    Tsur, O., Rappoport, A.: What’s in a hashtag?: content based prediction of the spread of ideas in microblogging communities. In: Proceedings of the Fifth ACM International Conference on Web Search and Data Mining, WSDM 2012, pp. 643–652. ACM, New York, NY, USA (2012). http://doi.acm.org/10.1145/2124295.2124320
  22. 22.
    TweetSmarter: The ultimate guide to finding the best time to tweet (2011). http://blog.tweetsmarter.com/retweeting/when-is-the-best-time-to-tweet/
  23. 23.
    Weng, L., Flammini, A., Vespignani, A., Menczer, F.: Competition among memes in a world with limited attention. Scientific reports 2 (2012)Google Scholar
  24. 24.
    Wikipedia: Levenshtein distance, July 2014Google Scholar
  25. 25.
    Wojnicki, A.C., Godes, D.: Word-of-mouth as self-enhancement. HBS marketing research paper (2008)Google Scholar
  26. 26.
    Yang, L., Sun, T., Zhang, M., Mei, Q.: We know what@ you# tag: does the dual role affect hashtag adoption? In: Proceedings of the 21st International Conference on World Wide Web. pp. 261–270. ACM (2012)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Nargis Pervin
    • 1
  • Tuan Quang Phan
    • 1
  • Anindya Datta
    • 1
  • Hideaki Takeda
    • 2
  • Fujio Toriumi
    • 3
  1. 1.National University of SingaporeSingaporeSingapore
  2. 2.National Institute of InformaticsTokyoJapan
  3. 3.The Tokyo UniversityTokyoJapan

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