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A novel algorithm for mining opinion leaders in social networks

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Abstract

Recently, social network analysis (SNA) has attracted researchers’ attention due to its practicability and popularity. Several mining techniques have been developed for extracting useful knowledge from users’ regularities. Opinion leader discovery is one essential task which has great commercial and political values. By identifying the opinion leaders, companies or governments could manipulate the selling or guiding public opinion, respectively. Additionally, detecting the influential comments is able to understand the source and trend of public opinion formation. However, mining opinion leaders in a huge social network is a challenge task because of the complexity of graph processing and leadership analysis. In this study, a novel algorithm, OLMiner, is proposed to efficiently find the opinion leaders from a social network. OLMiner utilizes a community detection method to tackle the influence overlapping issue and shrink the size of candidate generation. Then, we propose a novel clustering-based leadership analysis to find out the opinion leader in a social network. The experimental study shows that the proposed algorithm can effectively discover the influential opinion leaders in different real datasets with efficiency and has graceful scalability.

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References

  1. Bodendorf, F, Kaiser, C.: Detecting opinion leaders and trends in online social networks. Proceedings of the 2nd ACM Workshop on Social Web Search and Mining, pp. 65–68 (2009)

  2. Chen, Y., Zhu, W., Peng, W., Lee, W., Lee, S.: CIM: community-based influence maximization in social networks. ACM Trans. Intell. Syst. Technol. 5(2), 25 (2014)

    Article  Google Scholar 

  3. Cho, Y., Hwang, J., Lee, D.: Identification of effective opinion leaders in the diffusion of technological innovation: a social network approach. Technol. Forecast. Soc. Chang. 79(1), 97–106 (2012)

    Article  Google Scholar 

  4. Duan, J, Zeng, J, Luo, B: Identification of opinion leaders based on user clustering and sentiment analysis. Proceedings of the 2014 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT), pp. 377–383 (2014)

  5. Feng, Z., Xu, X., Yuruk, N., Schweiger, T.: A novel similarity-based modularity function for graph partitioning. In: Proceedings of the 9th International Conference on Data Warehousing and Knowledge Discovery (DaWaK’07), pp. 385–396 (2007)

    Chapter  Google Scholar 

  6. General Inquire. http://www.wjh.harvard.edu/~inquirer/

  7. HowNet. http://www.keenage.com/html/e_index.html

  8. Katz, E.: The two-step flow of communication: an up-to-date report on an hypothesis. Public Opin. Q. 21(1), 61–78 (1957)

    Article  Google Scholar 

  9. Ku, L., Chen, H.: Mining opinions from the Web: beyond relevance retrieval. J. Am. Soc. Inf. Sci. Technol. 58(12), 1838–1850 (2007)

    Article  Google Scholar 

  10. Ku, L., Ho, H., Chen, H.: Opinion mining and relationship discovery using CopeOpi opinion analysis system. J. Am. Soc. Inf. Sci. Technol. 60(7), 1486–14503 (2009)

    Article  Google Scholar 

  11. Li, F., Du, T.: Who is talking? An ontology-based opinion leader identification framework for word-of-mouth marketing in online social blogs. Decis. Support. Syst. 51(1), 190–197 (2011)

    Article  Google Scholar 

  12. Li, Y., Ma, S., Zhang, Y., Huang, R.: An improved mix framework for opinion leader identification in online learning communities. Knowl.-Based Syst. 43, 43–51 (2013)

    Article  Google Scholar 

  13. Liu, B., Zhang, L.: A survey of opinion mining and sentiment analysis. In: Mining Text Data, pp. 415–463 (2012)

    Chapter  Google Scholar 

  14. Liu, B, Hu, M, Cheng, J: Opinion observer: analyzing and comparing opinions on the Web. Proceedings of the 14th International Conference on World Wide Web, pp. 342–351 (2005)

  15. Miao, Q, Zhang, S, Meng, Y, Yu, H: Domain-sensitive opinion leader mining from online review communities. Proceedings of the 22nd international conference on World Wide Web companion, pp. 187–188 (2013)

  16. Mobile01. http://www.mobile01.com

  17. Princeton University “About WordNet.” WordNet. Princeton University (2010) http://wordnet.princeton.edu

  18. Song, K., Wang, D., Feng, S., Yu, G.: Detecting opinion leader dynamically in Chinese news comments. In: Web-Age Information Management, pp. 197–209. Springer (2012)

  19. Wan, L., Liao, J., Zhu, X.: Finding evaluating community structure in social networks. In: Proceedings of the 4th International Conference on Advanced Data Mining and Applications (ADMA’08), pp. 620–627 (2008)

    Chapter  Google Scholar 

  20. Yu, X., Wei, X., Lin, X.: Algorithms of BBS opinion leader mining based on sentiment analysis. In: Web Information Systems and Mining, pp. 360–369. Springer (2010)

  21. Zhai, Z., Xu, H., Jia, P.: Identifying opinion leaders in BBS. In: IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology, 2008. WI-IAT'08, vol. 3, pp. 398–401 (2008)

    Chapter  Google Scholar 

  22. Zhou, H., Zeng, D., Zhang, C.: Finding leaders from opinion networks. In: Intelligence and Security Informatics, 2009. ISI'09, pp. 266–268 (2009)

    Google Scholar 

Download references

Acknowledgements

Yi-Cheng Chen was supported in part by the Ministry of Science and Technology of Taiwan, Project, No. MOST 106-2221-E-008-104-MY2.

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Authors and Affiliations

  1. Department of Information Management, National Central University, Taoyuan, Taiwan

    Yi-Cheng Chen

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  1. Yi-Cheng Chen
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Correspondence to Yi-Cheng Chen.

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Guest Editors: Timothy K. Shih, Lin Hui, Somchoke Ruengittinun, and Qing Li

This article belongs to the Topical Collection: Special Issue on Social Media and Interactive Technologies

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Chen, YC. A novel algorithm for mining opinion leaders in social networks. World Wide Web 22, 1279–1295 (2019). https://doi.org/10.1007/s11280-018-0586-x

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  • DOI: https://doi.org/10.1007/s11280-018-0586-x

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