Abstract
Trust is context-dependent. In real-world scenarios, people trust each other only in certain contexts. However, this concept has not been seriously taken into account in most of the existing trust prediction approaches in Online Social Networks (OSNs). In addition, very few attempts have been made on trust prediction based on social psychology theories. For decades, social psychology theories have attempted to explain people’s behaviors in social networks; hence, employing such theories for trust prediction in OSNs will enhance accuracy. In this paper, we apply a well-known psychology theory, called Social Exchange Theory (SET), to evaluate the potential trust relation between users in OSNs. Based on SET, one person starts a relationship with another person, if and only if the costs of that relationship are less than its benefits. To evaluate potential trust relations in OSNs based on SET, we first propose some factors to capture the costs and benefits of a relationship. Then, based on these factors, we propose a trust metric called Trust Degree; at that point, we propose a trust prediction method, based on Matrix Factorization and apply the context of trust in a mathematical model. Finally, we conduct experiments on two real-world datasets to demonstrate the superior performance of our approach over the state-of-the-art approaches.
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References
Lenhart, A., Purcell, K., Smith, A., Zickuhr, K.: Social Media Mobile Internet Use Among Teens and Young Adults. Millennials. American Life Project, Washington DC (2010)
Abu-Salih, B., Wongthongtham, P., Beheshti, S., Zhu, D.: A preliminary approach to domain-based evaluation of users’ trustworthiness in online social networks. In: 2015 IEEE International Congress on Big Data, New York City, NY, USA, pp. 460–466 (2015)
Beheshti, A., Benatallah, B., Motahari-Nezhad, H.R.: ProcessAtlas: a scalable and extensible platform for business process analytics. Softw. Pract. Exp. 48(4), 842–866 (2018)
Beheshti, A., Benatallah, B., Nouri, R., Chhieng, V.M., Xiong, H., Zhao, X.: CoreDB: a data lake service. In: Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, CIKM 2017, Singapore, 06–10 November 2017, pp. 2451–2454 (2017)
Beheshti, A., Benatallah, B., Nouri, R., Tabebordbar, A.: CoreKG: a knowledge lake service. PVLDB 11(12), 1942–1945 (2018)
Beheshti, A., Vaghani, K., Benatallah, B., Tabebordbar, A.: CrowdCorrect: a curation pipeline for social data cleansing and curation. In: Mendling, J., Mouratidis, H. (eds.) CAiSE 2018. LNBIP, vol. 317, pp. 24–38. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-92901-9_3
Beheshti, S., Benatallah, B., Motahari-Nezhad, H.R.: Galaxy: a platform for explorative analysis of open data sources. In: Proceedings of the 19th International Conference on Extending Database Technology, EDBT 2016, Bordeaux, France, 15–16 March 2016, pp. 640–643 (2016)
Beheshti, S.-M.-R., Benatallah, B., Motahari-Nezhad, H.R., Sakr, S.: A query language for analyzing business processes execution. In: Rinderle-Ma, S., Toumani, F., Wolf, K. (eds.) BPM 2011. LNCS, vol. 6896, pp. 281–297. Springer, Heidelberg (2011). https://doi.org/10.1007/978-3-642-23059-2_22
Beheshti, S.-M.-R., et al.: Process Analytics: Concepts and Techniques for Querying and Analyzing Process Data. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-25037-3
Beheshti, S., Benatallah, B., Venugopal, S., Ryu, S.H., Motahari-Nezhad, H.R., Wang, W.: A systematic review and comparative analysis of cross-document coreference resolution methods and tools. Computing 99(4), 313–349 (2017)
Beheshti, S., Tabebordbar, A., Benatallah, B., Nouri, R.: On automating basic data curation tasks. In: Proceedings of the 26th International Conference on World Wide Web Companion, Perth, Australia, 3–7 April 2017, pp. 165–169 (2017)
Beigi, G., Tang, J., Wang, S., Liu, H.: Exploiting emotional information for trust/distrust prediction. In: Venkatasubramanian, S.C., Meira Jr., W. (eds.) Proceedings of the 2016 SIAM International Conference on Data Mining, USA, pp. 81–89. SIAM (2016)
Ding, C., Li, T., Jordan, M.I.: Nonnegative matrix factorization for combinatorial optimization. In: International Conference on Data Mining ICDM, Italy, pp. 183–192 (2008)
Sumner, C., Byers, A., Boovhever, R., Park, G.J.: Predicting dark triad personality traits from Twitter usage and a linguistic analysis of tweets. In: 11th International Conference on Machine Learning and Applications, ICMLA, USA, pp. 386–393 (2012)
Chen, S.D., Chen, Y., Han, J., Moulin, P.: A feature-enhanced ranking-based classifier for multimodal data and heterogeneous information networks. In: IEEE 13th International Conference on Data Mining, USA, pp. 997–1002 (2013)
Dunbar, R.I.M., Clark, A., Hurst, N.L.: Conflict and cooperation among the Vikings: contigent behavioural decisions. Ethol. Sociobiol. 16, 233 (1995)
Blau, P.M.: Exchange and power in social life. Soc. Forces 44(1), 128 (1965)
Liu, G., et al.: Context-aware trust network extraction in large-scale trust-oriented social networks. World Wide Web 21(3), 713 (2017)
Liu, G., Wang, Y., Orgun, M.A.: Social context-aware trust network discovery in complex contextual social networks. In: Proceedings of the 26 AAAI Conference, Canada (2012)
Golbeck, J.: Using trust and provenance for content filtering on the semantic web. In: Proceedings of the Workshop on Models of Trust on the Web, at the 15th WWW Conference (2006)
Liu, H., et al.: Predicting trusts among users of online communities: an epinions case study. In: EC, pp. 310–319 (2008)
Homans, G.C.: Social behavior as exchange. Am. J. Sociol. 63(6), 597 (1958)
Tang, J., Gao, H., Liu, H.: mtrust: discerning multi-faceted trust in a connected world. In: Proceedings of the Fifth WSDM, USA, pp. 93–102 (2012)
Tang, J., Gao, H., Hu, X., Liu, H.: Exploiting homophily effect for trust prediction. In: International Conference on Web Search and Data Mining, WSDM, Italy, pp. 53–62 (2013)
Jang, M.H., Faloutsos, C., Kim, S.W.: Trust prediction using positive, implicit, and negative information. In: Proceedings of the 23rd International Conference on World Wide Web, WWW 2014 Companion, USA, pp. 303–304 (2014)
Uddin, M.G., Zulkernine, M., Ahamed, S.I.: Cat: a context-aware trust model for open and dynamic systems. In: Proceedings of ACM Symposium on Applied Computing (SAC), pp. 2024–2029 (2008)
Maamar, Z., Sakr, S., Barnawi, A., Beheshti, S.-M.-R.: A framework of enriching business processes life-cycle with tagging information. In: Sharaf, M.A., Cheema, M.A., Qi, J. (eds.) ADC 2015. LNCS, vol. 9093, pp. 309–313. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-19548-3_25
Mayer, R.C., et al.: An integrative model of organizational trust. Acad. Manage. Rev. 20(3), 709 (1995)
Nowell, D.L., Kleinberg, J.M.: The link-prediction problem for social networks. JASIST 58, 1019 (2007)
Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web (WWW 2004), pp. 403–412 (2004)
Ghafari, S.M., Yakhchi, S., Beheshti, A., Orgun, M.: Social context-aware trust prediction: methods for identifying fake news. In: Hacid, H., Cellary, W., Wang, H., Paik, H.-Y., Zhou, R. (eds.) WISE 2018. LNCS, vol. 11233, pp. 161–177. Springer, Cham (2018). https://doi.org/10.1007/978-3-030-02922-7_11
Sanadhya, S., Singh, S.: Trust calculation with ant colony optimization in online social networks. Procedia Comput. Sci. 54, 186 (2015)
Surma, J.: Social exchange in online social networks: the reciprocity phenomenon on Facebook. Comput. Commun. 73, 342–346 (2016)
T. Althoff, P.J., Leskovec, J.: Online actions with offline impact: how online social networks influence online and offline user behavior. In: Proceedings of the Tenth ACM International Conference on Web Search and Data Mining, WSDM, United Kingdom, pp. 537–546 (2017)
Tabebordbar, A., Beheshti, A.: Adaptive rule monitoring system. In: Proceedings of the 1st International Workshop on Software Engineering for Cognitive Services, SE4COG@ICSE 2018, Gothenburg, Sweden, 28–29 May 2018, pp. 45–51 (2018)
Tang, J., Liu, H.: Trust in social media. Synthesis Lectures on Information Security. Priv. Trust 10, 1–29 (2015)
Thibaut, J., Kelley, H.: The Social Psychology of Groups. Wiley, New York (1959)
Zheng, X., Wang, Y., Orgun, M.A., Liu, G., Zhang, H.: Social context-aware trust prediction in social networks. In: Franch, X., Ghose, A.K., Lewis, G.A., Bhiri, S. (eds.) ICSOC 2014. LNCS, vol. 8831, pp. 527–534. Springer, Heidelberg (2014). https://doi.org/10.1007/978-3-662-45391-9_45
Wang, Y., Wang, X., Tang, J., Zuo, W., Cai, G.: Modeling status theory in trust prediction. In: Twenty-Ninth AAAI Conference on Artificial Intelligence, USA, pp. 1875–1881 (2015)
Wang, Y., Li, L., Liu, G.: Social context-aware trust inference for trust enhancement in social network based recommendations on service providers. World Wide Web 18, 159 (2015)
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The corresponding author has been receiving PhD top up scholarship from Data61 since July 2018.
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Ghafari, S.M., Yakhchi, S., Beheshti, A., Orgun, M. (2019). SETTRUST: Social Exchange Theory Based Context-Aware Trust Prediction in Online Social Networks. In: Hacid, H., Sheng, Q., Yoshida, T., Sarkheyli, A., Zhou, R. (eds) Data Quality and Trust in Big Data. QUAT 2018. Lecture Notes in Computer Science(), vol 11235. Springer, Cham. https://doi.org/10.1007/978-3-030-19143-6_4
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