f1b07955-98d8-4069-939f-b753fe26e42320220305073827527naun:naunmdt@crossref.orgMDT DepositInternational Journal of Communications1998-448010.46300/9107http://www.naun.org/cms.action?id=30333520223520221610.46300/9107.2022.16https://npublications.com/journals/communications/2022.phpAhmedAl-DhanhaniEtisalat BT Innovation Centre, Abu Dhabi, UAEHadiOtrokyKhalifa University of Science, Technology and Research, Abu Dhabi, UAERabebMizouniyKhalifa University of Science, Technology and Research, Abu Dhabi, UAEAhmadAl-RubaieEtisalat BT Innovation Centre, Abu Dhabi, UAESocial applications have witnessed a rapid growth in their use. Millions of people are utilizing them on a daily basis in order to share their experience, information and to communicate with their family members and friends. Lately, these technologies have been used to foster collaboration in education, however, it is a case of hit and miss and without established techniques to ensure or replicate success. One known problem that can impact the sustainability of collaborative social applications is the presence of selfish users. A selfish user adopts a free riding behaviour that takes advantage of the collaborative group without contributing back which would affect the group’s survivability. However, the inability to contribute back is not necessarily due to selfishness. In fact, cooperative learners may avoid participating due to the lack of expertise and/or confidence. In the literature, repeated non-cooperative game theory was introduced as a solution where several strategies were introduced to identify selfish users. However, such strategies do not differentiate between selfish learners and cooperative learners who are reluctant to answer others’ requests either due to lack of knowledge or confidence. In this paper, we show that educational and collaborative groups need to distinguish between those types of users and put in place mechanisms to encourage non contributing cooperative learners to participate rather than punishing them and excluding them from the group. An enhanced reputation-based Tit-for-Tat strategy is proposed as a solution that will enhance the group activity and overall gain.35202235202213183https://npublications.com/journals/communications/2022/a062006-003(2022).pdf10.46300/9107.2022.16.3https://npublications.com/journals/communications/2022/a062006-003(2022).pdf10.1007/s11257-011-9109-5J. Vassileva, “Motivating participation in social computing applications: a user modeling perspective,” User Modeling and User-Adapted Interaction, pp. 1–25, 2012. G. Hardin, “The tragedy of the commons,” New York, 1968. P. Kollock, “The economies of online cooperation: Gifts and public goods in cyberspace,” Communities in Cyberspace, pp. 220–239, 1999. 10.1016/0162-3095(92)90032-yR. Boyd and P. J. Richerson, “Punishment allows the evolution of cooperation (or anything else) in sizable groups,” Ethology and sociobiology, vol. 13, no. 3, pp. 171–195, 1992. 10.1007/978-3-642-02276-0_7P. Sloep, “Fostering sociability in learning networks through ad-hoc transient communities,” Computer-Mediated Social Networking, pp. 62– 75, 2009. R. Axelrod and W. Hamilton, “The evolution of cooperation,” Science, vol. 211, no. 4489, p. 1390, 1981. 10.4108/icst.collaboratecom.2012.250665A. Al-Dhanhani, R. Mizouni, H. Otrok, and A. Al-Rubai, “Game theoretical analysis of collaborative social applications,” in Collaborative Computing: Networking, Applications and Worksharing (CollaborateCom), 2012 8th International Conference on, pp. 628–634, IEEE, 2012. 10.1109/hicss.2007.39Y. Mao, J. Vassileva, and W. Grassmann, “A system dynamics approach to study virtual communities,” in System Sciences, 2007. HICSS 2007. 40th Annual Hawaii International Conference on, pp. 178a–178a, IEEE, 2007. Y. Ren and R. Kraut, “A simulation for designing online community: Member motivation, contribution, and discussion moderation,” Information Systems Research, 2011. 10.1109/comst.2005.1593279V. Srivastava, J. Neel, A. MacKenzie, R. Menon, L. DaSilva, J. Hicks, J. Reed, and R. Gilles, “Using game theory to analyze wireless ad hoc networks,” Communications Surveys & Tutorials, IEEE, vol. 7, no. 4, pp. 46–56, 2005. 10.1016/j.comnet.2011.11.013J. Robert, H. Otrok, A. Quttoum, and R. Boukhris, “A distributed resource management model for virtual private networks: Tit-for-tat strategies,” Computer Networks, 2011. 10.1109/iciw.2008.12D. Peng, W. Liu, C. Lin, Z. Chen, and X. Peng, “Enhancing tit-for-tat strategy to cope with free-riding in unreliable p2p networks,” in Internet and Web Applications and Services, 2008. ICIW’08. Third International Conference on, pp. 336–341, IEEE, 2008.