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A social recommendation method based on opinion leaders

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Abstract

With the rapid development of information technology, social media has been widely used, and Internet information has been exploded, and consumers may experience information overload. Recommender systems using the social recommendation method that integrates social relationship information can provide users with target information that meets their needs. However, most of the existing methods only rely on the user’s ordinary friends to make recommendations, neglecting another influential group, the opinion leaders. In this study, we propose a new social recommendation method based on opinion leaders. The proposed method assumes that the influence of the opinion leader on the user is much greater than that of the user’s ordinary friends. The experimental results on two real datasets show that the proposed method not only has a better recommendation effect than the state-of-the-art recommendation algorithms, but also has a good performance in the cases of cold-start users.

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References

  1. Casaló LV, Flavián C, Ibáñez-Sánchez S (2018) Influencers on Instagram: antecedents and consequences of opinion leadership. J Bus Res 92:168–178

    Article  Google Scholar 

  2. Chen T, Zhu Q, Zhou M et al (2017) Trust-based recommendation algorithm in social network. Journal of Software 28(3):721–731

    MATH  Google Scholar 

  3. Guo G, Jie Z, Thalmann D et al (2014). ETAF: an extended trust antecedents framework for trust prediction. In: proceedings of the 6th IEEE /ACM international conference on advances in social networks analysis and mining, pp 540–547

  4. Guo L, Ma J, Chen Z (2013) Trust strength aware social recommendation method. Journal of Computer Research and Development 50(9):1805–1813

    Google Scholar 

  5. Guo L, Ma J, Chen Z et al (2014) Incorporating item relations for social recommendation. Chinese Journal of Computers 37(1):219–228

    Google Scholar 

  6. Guo G, Zhang J, Thalmann D (2014) Merging trust in collaborative filtering to alleviate data sparsity and cold start. Knowl-Based Syst 57:57–68

    Article  Google Scholar 

  7. Guo G, Zhang J, Yorke-Smith N (2016) A novel evidence-based bayesian similarity measure for recommender systems. ACM Trans Web 10(2):1–30

    Article  Google Scholar 

  8. Guo G, Zhang J, Zhu F, Wang X (2017) Factored similarity models with social trust for top-n item recommendation. Knowl-Based Syst 122:17–25

    Article  Google Scholar 

  9. Huang S, Zhang J, Wang L et al (2015) Social friend recommendation based on multiple network correlation. IEEE Transactions on Multimedia 18(2):287–299

    Article  Google Scholar 

  10. Huhn R, Brantes Ferreira J, Angilberto SDF et al (2018) The effects of social media opinion leaders' recommendations on followers’ intention to buy. Review of Business Management 20(1):57–73

    Article  Google Scholar 

  11. Jain L, Katarya R, Sachdeva S (2020) Opinion leader detection using whale optimization algorithm in online social network. Expert Syst Appl 142:113016

    Article  Google Scholar 

  12. Jamali M, Ester M (2010) A matrix factorization technique with trust propagation for recommendation in social networks. In: Proceedings of the 4th ACM conference on recommender systems. ACM, New York, pp 135–142

    Chapter  Google Scholar 

  13. Lazarsfeld PF, Berelson B, Gaudet H (1950) The people's choice. Eco-Architecture: Harmonisation between Architecture and Nature 18:154

    Google Scholar 

  14. Liu D, Jie H, Chen L (2018) Recommendation with social roles. IEEE Access 6(99):36420–36427

    Article  Google Scholar 

  15. Ma H, King I, Lyu MR (2009) Learning to recommend with social trust ensemble. In: Proceedings of the 32nd international ACM SIGIR conference on Research and Development in information retrieval. ACM, New York, pp 203–210

    Chapter  Google Scholar 

  16. Ma H, Yang H, Lyu MR et al (2008) Sorec: social recommendation using probabilistic matrix factorization. In: Proceedings of the 17th ACM conference on information and knowledge management. ACM, New York, pp 931–940

    Chapter  Google Scholar 

  17. Ma H, Zhou D, Liu C et al (2011) Recommender systems with social regularization. In: Proceedings of the 4th ACM international conference on web search and data mining. ACM, New York, pp 287–296

    Chapter  Google Scholar 

  18. Mao M, Lu J, Zhang G et al (2016) Multirelational social recommendations via multigraph ranking. IEEE Transactions on Cybernetics 47(12):1–13

    Google Scholar 

  19. Meng X, Liu S, Zhang Y et al (2015) Research on social recommender systems. Journal of Software 26(6):1356–1372

    MathSciNet  Google Scholar 

  20. Pan Y, He F, Yu H (2018) Social recommendation algorithm using implicit similarity in trust. Chinese Journal of Computers 41(1):65–81

    Google Scholar 

  21. Qiu L, Dai J, Liu H et al (2018) Detecting opinion leaders in online social networks using HybridRank algorithm. J Intell Fuzzy Syst 35(1):513–522

    Article  Google Scholar 

  22. Quijano-Sanchez L, Recio-Garcia JA, Diaz-Agudo B, Jimenez-Diaz G (2013) Social factors in group recommender systems. ACM Trans Intell Syst Technol 4(1):1–30

    Article  Google Scholar 

  23. Riquelme F, Gonzalez-Cantergiani P, Hans D, Villarroel R, Munoz R (2019) Identifying opinion leaders on social networks through milestones definition. IEEE Access 7:75670–75677

    Article  Google Scholar 

  24. Salakhutdinov R, Mnih A (2008) Probabilistic matrix factorization. In: Proceedings of the 21st annual conference on neural information proceeding system. Curran Associates, New York, pp 1257–1264

    Google Scholar 

  25. Sun G, Bin S (2018) A new opinion leaders detecting algorithm in multi-relationship online social networks. Multimed Tools Appl 77(4):4295–4307

    Article  Google Scholar 

  26. Turcotte J, York C, Irving J, Scholl RM, Pingree RJ (2015) News recommendations from social media opinion leaders: effects on media trust and information seeking. J Comput-Mediat Commun 20(5):520–535

    Article  Google Scholar 

  27. Wang J, Ding K, Zhu Z et al (2020) Key opinion leaders in recommendation systems: opinion elicitation and diffusion. In: proceedings of the 13th ACM international conference on web search and data mining, pp 636–644

  28. Wang X, Liu Y, Xiong F (2016) Improved personalized recommendation based on a similarity network. Physica A: Statistical Mechanics and its Applications 456:271–280

    Article  Google Scholar 

  29. Wang Z, Sun L, Zhu W, Yang S, Li H, Wu D (2013) Joint social and content recommendation for user-generated videos in online social network. IEEE Transactions on Multimedia 15(3):698–709

    Article  Google Scholar 

  30. Wu B, Zhou X, Jin Q (2015) Participatory information search and recommendation based on social roles and networks. Multimed Tools Appl 74(14):5173–5188

    Article  Google Scholar 

  31. Xiong F, Wang XM, Pan SR et al (2018) Social recommendation with evolutionary opinion dynamics. IEEE Transactions on Systems, Man, and Cybernetics: Systems 48:1–13

    Article  Google Scholar 

  32. Yang B, Lei Y, Liu J, Li W (2017) Social collaborative filtering by trust. IEEE Trans Pattern Anal Mach Intell 39(8):1633–1647

    Article  Google Scholar 

  33. Yao W, He J, Huang G et al (2014) Modeling dual role preferences for trust-aware recommendation. In: proceedings of the 37th international ACM SIGIR conference on Research and Development in information retrieval, pp 975–978

  34. Yi-cheng C (2019) A novel algorithm for mining opinion leaders in social networks. World Wide Web 22(3):1279–1295

    Article  Google Scholar 

  35. Zhang K, Liang J, Zhao X et al (2018) A collaborative filtering recommendation algorithm based on information of community expert. Journal of Computer Research and Development 55(05):78–86

    Google Scholar 

  36. Zhou X, Wu B, Jin Q et al (2014) Social stream organization based on user role analysis for participatory information recommendation. In: International Conference on Ubi-media Computing and Workshops, pp 105–110

  37. Zhu Y, Lv L (2012) Evaluation metrics for recommender systems. Journal of University of Electronic Science & Technology of China 41(2):163–175

    Google Scholar 

Download references

Acknowledgments

This research was supported by the National Natural Science Foundation of China Youth Program (61300104), Doctoral Research Start-Up Project of Longyan University (LB2020003) and Natural Science Foundation of Fujian Province, China(2018 J01791).

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Correspondence to Qishan Zhang.

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Weng, L., Zhang, Q. A social recommendation method based on opinion leaders. Multimed Tools Appl 80, 5857–5872 (2021). https://doi.org/10.1007/s11042-020-09972-6

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