An Adaptive Distributed Consumer Trust Model for Social Commerce

References

• Accenture. 2022. Why shopping’s set for a social revolution. Accessed June 6, 2023. https://www.accenture.com/us-en/insights/software-platforms/why-shopping-set-social-revolution.
   Google Scholar
• Adamopoulou, A. A., and A. L. Symeonidis. 2014. A simulation testbed for analyzing trust and reputation mechanisms in unreliable online markets. Electronic Commerce Research and Applications 13 (5):368–34. doi:10.1016/j.elerap.2014.07.001.
   Web of Science ®Google Scholar
• Al-Adwan, A. S., and H. Yaseen. 2023. Solving the product uncertainty hurdle in social commerce: The mediating role of seller uncertainty. International Journal of Information Management Data Insights 3 (1):1–16. doi:10.1016/j.jjimei.2023.100169.
   Google Scholar
• Botelho, V., F. Enembreck, B. C. Avila, H. de Azevedo, and E. E. Scalabrin. 2009. Encrypted certified trust in multi-agent system. Proceedings of the 13th International Conference on Computer Supported Cooperative Work in Design, 227–32. doi:10.1109/CSCWD.2009.4968063.
   Google Scholar
• Chamba-Eras, L., A. Arruarte, and J. A. Elorriaga. 2023. T-VLC: A trust model for virtual learning communities. IEEE Transactions on Learning Technologies 16 (5):847–60. doi:10.1109/TLT.2023.3288363.
   Web of Science ®Google Scholar
• Chen, G. Z., F. P. Zeng, J. Zhang, T. T. Lu, J. F. Shen, and W. J. Shu. 2021. An adaptive trust model based on recommendation filtering algorithm for the internet of things systems. Computer Networks 190:107952. doi:10.1016/j.comnet.2021.107952.
   Web of Science ®Google Scholar
• DePaulo, B. M., and D. A. Kashy. 1998. Everyday lies in close and casual relationships. Journal of Personality & Social Psychology 74 (1):63–79. doi:10.1037/0022-3514.74.1.63.
   PubMed Web of Science ®Google Scholar
• Fakespot. 2021. Let’s talk about fake reviews. Accessed October 1, 2023. https://www.fakespot.com/post/lets-talk-about-fake-reviews-part-1.
   Google Scholar
• Fang, H., J. Zhang, and M. Sensoy. 2018. A generalized stereotype learning approach and its instantiation in trust modeling. Electronic Commerce Research and Applications 30:149–58. doi:10.1016/j.elerap.2018.06.004.
   Web of Science ®Google Scholar
• Fang, H., J. Zhang, and M. Sensoy. 2020. A 2020 perspective on “A generalized stereotype learning approach and its instantiation in trust modeling”. Electronic Commerce Research and Applications 40:40. doi:10.1016/j.elerap.2020.100955.
   Web of Science ®Google Scholar
• Gan, Z. B., Q. Ding, K. Li, and G. Q. Xiao. 2011. Reputation-based multi-dimensional trust algorithm. Journal of Software 22 (10):2401–11. doi:10.3724/SP.J.1001.2011.03909.
   Google Scholar
• García, J. J. L., D. Lizcano, C. M. Ramos, and N. Matos. 2019. Digital marketing actions that achieve a better attraction and loyalty of users: An analytical study. Future Internet 11 (6):130. doi:10.3390/fi11060130.
   Web of Science ®Google Scholar
• Gong, Y. H., L. Chen, T. H. Ma, and V. S. Sheng. 2020. A comprehensive trust model based on social relationship and transaction attributes. Security and Communication Networks 2020:1–10. doi:10.1155/2020/8887596.
   Web of Science ®Google Scholar
• Hosseinnezhad, M., M. A. Azgomi, and M. R. E. Dishabi. 2024. A probabilistic trust model for cloud services using bayesian networks. Soft Computing 28 (1):509–26. doi:10.1007/s00500-023-08264-z.
   Web of Science ®Google Scholar
• Hui, H. W., Z. X. Gong, J. W. An, and J. Z. Qi. 2023. A dynamic bayesian-based comprehensive trust evaluation model for dispersed computing environment. China Communications 20 (2):278–88. doi:10.23919/JCC.2023.02.018.
   Web of Science ®Google Scholar
• Huynh, T. D., N. R. Jennings, and N. R. Shadbolt. 2005. On handling inaccurate witness reports. 8th Int. Workshop on Trust in Agent Societies (TRUST), Utrecht, Netherlands.
   Google Scholar
• Huynh, T. D., N. R. Jennings, and N. R. Shadbolt. 2006. An integrated trust and reputation model for open multi-agent systems. Autonomous Agents and Multi-Agent Systems 13 (2):119–54. doi:10.1007/s10458-005-6825-4.
   Web of Science ®Google Scholar
• Ji, S. J., Q. Zhang, J. P. Li, D. K. W. Chiu, S. H. Xu, L. Yi, and M. G. Gong. 2020. A burst-based unsupervised method for detecting review spammer groups. Information Sciences 536:454–69. doi:10.1016/j.ins.2020.05.084.
   Web of Science ®Google Scholar
• Knoke, D. 2001. Changing organizations: Business networks in the new political economy. New York: Westview Press.
   Google Scholar
• Leong, L. Y., T. S. Hew, K. B. Ooi, and A. Y. L. Chong. 2020. Predicting the antecedents of trust in social commerce – a hybrid structural equation modeling with neural network approach. Journal of Business Research 110:24–40. doi:10.1016/j.jbusres.2019.11.056.
   Web of Science ®Google Scholar
• Li, Y. J., F. X. Wang, S. W. Zhang, and X. F. Niu. 2021. Detection of fake reviews using group model. Mobile Networks & Applications 26 (1):91–103. doi:10.1007/s11036-020-01688-z.
   Web of Science ®Google Scholar
• Liu, B. 2020. A survey on trust modeling from a Bayesian perspective. Wireless Personal Communications 112 (2):1205–27. doi:10.1007/s11277-020-07097-5.
   Web of Science ®Google Scholar
• Liu, G. F., Y. Wang, M. A. Orgun, and E. P. Lim. 2013. Finding the optimal social trust path for the selection of trustworthy service providers in complex social networks. IEEE Transactions on Services Computing 6 (2):152–67. doi:10.1109/TSC.2011.58.
   Web of Science ®Google Scholar
• Liu, X., A. Datta, and K. Rzadca. 2013. Trust beyond reputation: A computational trust model based on stereotypes. Electronic Commerce Research and Applications 12 (1):24–39. doi:10.1016/j.elerap.2012.07.001.
   Web of Science ®Google Scholar
• Miller, R. S., and H. M. Lefcourt. 1982. The assessment of social intimacy. Journal of Personality Assessment 46 (5):514–18. doi:10.1207/s15327752jpa4605_12.
   PubMed Web of Science ®Google Scholar
• Mujawar, T. N., and L. B. Bhajantri. 2022. Behavior and feedback based trust computation in cloud environment. Journal of King Saud University - Computer and Information Sciences 34 (8):4956–67. doi:10.1016/j.jksuci.2020.12.003.
   Web of Science ®Google Scholar
• Pearl, J. 1988. Probabilistic reasoning in intelligent systems: Networks of plausible inference. San Francisco, CA: Morgan Kaufmann.
   Google Scholar
• Pinyol, I., J. Sabater, P. Dellunde, and M. Paolucci. 2012. Reputation-based decisions for logic-based cognitive agents. Autonomous Agents and Multi-Agent Systems 24 (1):175–216. doi:10.1007/s10458-010-9149-y.
   Web of Science ®Google Scholar
• Ramchurn, S. D., T. D. Huynh, and N. R. Jennings. 2004. Trust in multi-agent systems. The Knowledge Engineering Review 19 (1):1–25. doi:10.1017/S0269888904000116.
   Web of Science ®Google Scholar
• Sabater, J., and C. Sierra. 2002. Reputation and social network analysis in multi-agent systems. International Conference on Autonomous Agents and Multiagent Systems (AAMAS). doi:10.1145/544741.544854.
   Google Scholar
• Sabater, J., and C. Sierra. 2005. Review on computational trust and reputation models. Artificial Intelligence Review 24 (1):33–60. doi:10.1007/s10462-004-0041-5.
   Web of Science ®Google Scholar
• Sharma, S., P. Menard, and L. A. Mutchler. 2019. Who to trust? Applying trust to social commerce. Journal of Computer Information Systems 59 (1):32–42. doi:10.1080/08874417.2017.1289356.
   Web of Science ®Google Scholar
• Shehada, D., C. Yeun, M. Zemerly, M. Al-Qutayri, Y. Al-Hammadi, and J. K. Hu. 2018. A new adaptive trust and reputation model for mobile agent systems. Journal of Network and Computer Applications 124:33–43. doi:10.1016/j.jnca.2018.09.011.
   Web of Science ®Google Scholar
• Statista. 2020. Share of amazon shoppers in the United States who trust product reviews on amazon as of February 2020. Accessed January 1, 2023. https://www.statista.com/statistics/623659/amazon-customer-review-usage-usa/.
   Google Scholar
• Sutton, R. S., and A. G. Barto. 2018. Reinforcement learning: An introduction, 2nd ed. Cambridge, MA: MIT Press.
   Google Scholar
• Taylor, P., N. Griffiths, L. Barakat, and S. Miles. 2017. Stereotype reputation with limited observability. International Conference on Autonomous Agents and Multiagent Systems (AAMAS). doi:10.1007/978-3-319-71682-4_6.
   Google Scholar
• Tijsma, A. D., M. M. Drugan, and M. A. Wiering. 2017. Comparing exploration strategies for Q-learning in random stochastic mazes. IEEE Symposium Series on Computational Intelligence (IEEE SSCI). doi:10.1109/SSCI.2016.7849366.
   Google Scholar
• Wang, N. K., D. J. Wei, H. Mi, J. Zang, and S. Wang. 2022. Analysis of carbon emission energy inventory from refrigerant production and recycling carbon compensation. Applied Sciences 12 (1):1–26. doi:10.3390/app12010001.
   Google Scholar
• Wang, Y., L. Q. Tian, and Z. N. Wu. 2021. Trust modeling based on probabilistic linguistic term sets and the MULTIMOORA method. Expert Systems with Applications 165:113817. doi:10.1016/j.eswa.2020.113817.
   Web of Science ®Google Scholar
• Wu, T., X. Liu, and J. D. Qin. 2019. An interval type-2 fuzzy trust evaluation model in social commerce. Computational Intelligence 35 (4):1113–31. doi:10.1111/coin.12239.
   Web of Science ®Google Scholar
• Wu, Z. N., L. Q. Tian, Y. Zhang, and Z. G. Wang. 2021. Web user trust evaluation: A novel approach using fuzzy petri net and behavior analysis. Symmetry 13 (8):1–15. doi:10.3390/sym13081487.
   Google Scholar
• Xu, G. Q., G. X. Zhang, C. Xu, B. Liu, M. Q. Li, Y. Ren, X. H. Li, Z. Y. Feng, and D. G. Zhang. 2017. A multi-attribute rating based trust model: Improving the personalized trust modeling framework. Multimedia Tools & Applications 76 (4):5833–49. doi:10.1007/s11042-015-2539-z.
   Web of Science ®Google Scholar
• Yadav, M. S., K. de Valck, T. Hennig-Thurau, D. L. Hoffman, and M. Spann. 2013. Social commerce: A contingency framework for assessing marketing potential. Journal of Interactive Marketing 27 (4):311–23. doi:10.1016/j.intmar.2013.09.001.
   Web of Science ®Google Scholar
• You, X. L., F. J. Hou, and F. Chiclana. 2024. A reputation-based trust evaluation model in group decision-making framework. Information Fusion 103:102082. doi:10.1016/j.inffus.2023.102082.
   Web of Science ®Google Scholar
• Yu, B., and M. P. Singh. 2002. An evidential model of distributed reputation management. International Conference on Autonomous Agents and Multiagent Systems (AAMAS). doi:10.1145/544741.544809.
   Google Scholar
• Yu, B., and M. P. Singh. 2003a. Detecting deception in reputation management. International Conference on Autonomous Agents and Multiagent Systems (AAMAS). doi:10.1145/860575.860588.
   Google Scholar
• Yu, B., and M. P. Singh. 2003b. Searching social networks. International Conference on Autonomous Agents and Multiagent Systems (AAMAS). doi:10.1145/860575.860587.
   Google Scholar
• Zacharia, G., and P. Maes. 2000. Trust management through reputation mechanisms. Applied Artificial Intelligence 14 (9):881–907. doi:10.1080/08839510050144868.
   Web of Science ®Google Scholar
• Zhang, J., and R. Cohen. 2008. Evaluating the trustworthiness of advice about seller agents in e-marketplaces: A personalized approach. Electronic Commerce Research and Applications 7 (3):330–40. doi:10.1016/j.elerap.2008.03.001.
   Web of Science ®Google Scholar
• Zhao, W. J., F. Hu, J. Wang, T. Shu, and Y. Xu. 2023. A systematic literature review on social commerce: Assessing the past and guiding the future. Electronic Commerce Research and Applications 57:1–12. doi:10.1016/j.elerap.2022.101219.
   Web of Science ®Google Scholar
• Zhou, S., G. Zhang, and X. F. Meng. 2022. LocTrust: A local and global consensus-combined trust model in MANETs. Peer-To-Peer Networking and Applications 15 (1):355–68. doi:10.1007/s12083-021-01250-y.
   Web of Science ®Google Scholar