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The Three-Degree Calculation Model of Microblog Users’ Influence (Short Paper)

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Collaborative Computing: Networking, Applications and Worksharing (CollaborateCom 2018)

Abstract

Highly influential social users can guide public opinion and influence their emotional venting. Therefore, it is of great significance to identify high-impact users effectively. This paper starts with the users’ text content, users’ emotions, and fans’ behaviors. It combines the amount of information in the content and sentiment tendency with the fans’ forwarding, commenting, and Liking actions. And based on the principle of the three-degree influence, the users’ influence calculation model is constructed. Finally, the experimental results show that the three-degree force calculation model is more accurate and effective than other similar models.

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References

  1. Triplett, N.: The dynamogenic factors in pacemaking and competition. Am. J. Psychol. 9(4), 507–533 (1970)

    Article  Google Scholar 

  2. Katz, E., Lazarsfeld, P.F.: Personal influence: the part played by people in the flow of mass communications. Am. J. Sociol. 21(6), 1583–1583 (1955)

    Google Scholar 

  3. Zhang, J., Tang, J.: A review of social influence analysis. Chin. Sci. Inf. Sci. 47(08), 967–979 (2017)

    Google Scholar 

  4. Shi, C., Tang, J., Hu, Y.: Predicting microblog user influence based on user behavior and blog content. J. Chin. Comput. Syst. 38(07), 1495–1500 (2017)

    Google Scholar 

  5. Chen, Z., Liu, X., Li, B.: Analysis of influence of microblog users communication based on behavior and community. J. Comput. 35(07), 1–6 (2018)

    Google Scholar 

  6. Kang, S., Zhang, C., Lin, Z., Shi, X., Ma, H.: Complexity research of massively microblogging based on human behaviors. In: Proceedings of the International Workshop on Database Technology and Applications, Wuhan, China, 27–28 November 2010, pp. 1–4. IEEE, New York (2010)

    Google Scholar 

  7. Xu, D., Liu, Y., Zhang, M., Ma, S.: Research on user influence based on online social network. J. Chin. Inf. Process. 30(02), 83–89 (2016)

    Google Scholar 

  8. Fowler, J.H., Christakis, N.A.: Dynamic spread of happiness in a large social network: longitudinal analysis over 20 years in the Framingham heart study. BMJ 337, a2338 (2008)

    Article  Google Scholar 

  9. Ili\(\acute{\rm c}\), J., et al.: Proof of concept for comparison and classification of online social network friends based on tie strength calculation model. In: Zdravkovi\(\acute{\rm c}\), M., Trajnovi\(\acute{\rm c}\), M., Konjovi\(\acute{\rm c}\), Z. (eds.) Proceedings ICIST 2016 (2016)

    Google Scholar 

  10. Al-Ghaith, W.: Understanding social network usage: impact of co-presence, intimacy, and immediacy. Int. J. Adv. Comput. Sci. Appl. 6(8), 99–111 (2015)

    Google Scholar 

  11. Li, R., Zhang, H., Zhao, Y., Shang, J.: Research on automatic abstracting technology of Chinese documents based on topic model and information entropy. Comput. Sci. 41, 298–300 (2014)

    Google Scholar 

  12. Feng, S., Fu, Y., Yang, F., Wang, D., Zhang, Y.: Analysis of Bowen affective tendency based on dependency syntax. J. Comput. Res. 49, 2395–2406 (2012)

    Google Scholar 

  13. Liu, F., Wang, L., Gao, L., et al.: A web service trust evaluation model based on small-world networks. Knowl.-Based Syst. 57(2), 161–167 (2014)

    Article  Google Scholar 

  14. Hu, M., Yao, T.: Chinese micro blog view sentence recognition and evaluation object extraction method. J. Shandong Univ. (Sci. Edn.) 51(07), 81–89 (2016)

    Google Scholar 

  15. Liu, F., Wang, L., Johnson, H., Zhao, H.: Analysis of network trust dynamics based on evolutionary game. Sci. Iranica Trans. E: Ind. Eng. 22(6), 2548–2557 (2015)

    Google Scholar 

  16. Paltoglou, G., Thelwall, M.: A study of information retrieval weighting schemes for sentiment analysis. In: Meeting of the Association for Computational Linguistics, 11–16 July, Uppsala, Sweden, 1386–1395. DBLP (2010)

    Google Scholar 

  17. Zhang, H., Li, H., Li, Q.: Research on automatic calculation algorithm of emotional word discovery and polarity weight. J. Chin. Inf. Process. 31(03), 48–54 (2017)

    Google Scholar 

  18. Zhao, J., Liu, Y., Li, X., Wang, M., Mo, S.: The evaluation method of node influence based on the third degree theory. J. Fuyang Teach. Coll. 33(04), 78–82 (2016)

    Google Scholar 

  19. Hou, W., Huang, Y., Zhang, K.: Research of micro-blog diffusion effect based on analysis of retweet behavior. In: International Conference on Cognitive Informatics and Cognitive Computing, pp. 255–261. IEEE (2015)

    Google Scholar 

  20. Li, X, Cheng, S., Chen, W., et al.: Novel user influence measurement based on user interaction in microblog. In: International Conference on Advances in Social Networks Analysis and Mining, pp. 615–619. IEEE (2013)

    Google Scholar 

  21. Huang, Y., Li, L.: Analysis of user influence in social network based on behavior and relationship. In: International Conference on Measurement, Information and Control, Harbin, pp. 682–686, August 2013

    Google Scholar 

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Correspondence to Fu Xie .

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© 2019 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Sun, X., Xie, F. (2019). The Three-Degree Calculation Model of Microblog Users’ Influence (Short Paper). In: Gao, H., Wang, X., Yin, Y., Iqbal, M. (eds) Collaborative Computing: Networking, Applications and Worksharing. CollaborateCom 2018. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 268. Springer, Cham. https://doi.org/10.1007/978-3-030-12981-1_10

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  • DOI: https://doi.org/10.1007/978-3-030-12981-1_10

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-12980-4

  • Online ISBN: 978-3-030-12981-1

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