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Influence Diffusion Detection Using Blogger’s Influence Style

  • Luke Kien-Weng Tan
  • Jin-Cheon Na
  • Yin-Leng Theng
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8279)

Abstract

Previous studies on detecting blogosphere influence diffusion had used blog features such as in-degree and sentiment links. The approaches in most of these studies assumed that influence increases with the number of links and largely ignored the possible effect of bloggers’ influence style on the diffusion of influence between linked bloggers where influence could be further described through the engagement style, persuasion style, and the persona of the bloggers. In this paper, we propose an Influence Diffusion Detection Model – Influence Style (IDDM-IS) that includes the use of bloggers’ influence styles to detect influence diffusion through the blogosphere. Our study analyzed 107 bloggers with varying influence styles to detect the influence diffusion path. The results showed performance for IDDM-IS to be better than the in-degree and sentiment-values baseline approaches. In addition, IDDM-IS could provide a fine-grained description of the influence diffusion paths using the bloggers’ influence styles.

Keywords

Influence diffusion detection influence style profiling blogger influence 

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References

  1. 1.
    Adar, E., Adamic, L.A.: Tracking Information Epidemics in Blogspace. In: Conference on Web Intelligence, pp. 207–214 (2005)Google Scholar
  2. 2.
    Agarwal, N., Liu, H.: Modeling and Data Mining in Blogosphere. Morgan & Claypool (2009)Google Scholar
  3. 3.
    Cai, K.K., Bao, S.H., Yang, Z., Tang, J., Ma, R., Zhang, L., Su, Z.: OOLAM: An Opinion Oriented Link Analysis Model for Influence Persona Discovery. In: Web Search and Data Mining, pp. 645–654 (2011)Google Scholar
  4. 4.
    Cohen, J.A.: Coefficient of Agreement for Nominal Scales. Educational and Psychological Measurement 20(1), 37–46 (1960)CrossRefGoogle Scholar
  5. 5.
    Costa Jr., P.T., McCrae, R.R.: Normal personality assessment in clinical practice: The NEO Personality Inventory. Psychological Assessment 4, 5–3 (1992)Google Scholar
  6. 6.
    Goldenberg, J., Libai, B., Muller, E.: Talk of the Network: A Complex Systems Look at the Underlying Process of Word-of-Mouth. Marketing Letters 12(3), 211–223 (2001)CrossRefGoogle Scholar
  7. 7.
    Granovetter, M.: Threshold models of collective behavior. American Journal of Sociology 83(6), 1420–1443 (1978)CrossRefGoogle Scholar
  8. 8.
    Gruhl, D., Guha, R., Liben-Nowell, D., Tomkins, A.: Information diffusion through blogspace. In: Proceedings of the 13th International Conference on World Wide Web, pp. 491–501 (2004)Google Scholar
  9. 9.
    Guadagno, R.E., Okdie, B.M., Eno, C.A.: Who blogs? Personality predictors of blogging. Computers in Human Behavior 24(5) (2008)Google Scholar
  10. 10.
    Leskovec, J., Huttenlocher, D., Kleinberg, J.: Predicting Positive and Negative Links in Online Social Networks. In: World Wide Web, pp. 641–650 (2010)Google Scholar
  11. 11.
    Lim, S.-H., Kim, S.-W., Kim, S., Park, S.: Construction of a blog network based on information diffusion. In: Proceedings of the 2011 ACM Symposium on Applied Computing, pp. 937–941 (2011)Google Scholar
  12. 12.
    Matsumura, N., Yamamoto, H., Tomozawa, D.: Finding Influencers and Consumer Insights in the Blogosphere. In: International Conference on Weblogs and Social Media AAAI, pp. 76–83 (2008)Google Scholar
  13. 13.
    Tan, L.K.W., Na, J.-C., Theng, Y.-L., Chang, K.Y.: Blog Site Profiling through Influence Style Detection. In: International Conference on Asian Digital Libraries ACM, pp. 329–332 (2012)Google Scholar
  14. 14.
    Wilson, T., Wiebe, J., Hoffmann, P.: Recognizing Contextual Polarity in Phrase-Level Sentiment Analysis. In: Human Language Technology Conference on Empirical Methods in Natural Language Processing ACL, pp. 347–354 (2005)Google Scholar
  15. 15.
    Yarkoni, T.: Personality in 100,000 words: A large-scale analysis of personality and word use among bloggers. Journal of Research in Personality (2010)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2013

Authors and Affiliations

  • Luke Kien-Weng Tan
    • 1
  • Jin-Cheon Na
    • 1
  • Yin-Leng Theng
    • 1
  1. 1.Wee Kim Wee School of Communication and InformationNanyang Technological UniversitySingapore

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