Opinion Leader’s Selection with Grey Wolf Optimizer Algorithm on Social Networks
محورهای موضوعی : مجله بین المللی ریاضیات صنعتی
S. Mohammad Aghdam
1
(
Department of Computer Engineering, Urmia Branch, Islamic Azad University, Urmia, Iran.
)
F. Soleimanian Gharehchopogh
2
(
Department of Computer Engineering, Urmia Branch, Islamic Azad University, Urmia, Iran.
)
M. Masdari
3
(
Department of Computer Engineering, Urmia Branch, Islamic Azad University, Urmia, Iran.
)
کلید واژه: Grey Wolf Optimizer Algorithm, Opinion Leader, Social Networks, Virtual Communities, leadership,
چکیده مقاله :
Opinion leaders in social networks are beneficial and we will be able to use their empowerment and influence by identifying them. In this paper, we have chosen the opinion leaders with Grey Wolf Optimizer (GWO) algorithm. The results show, the number of actual opinion leaders identified by this algorithm is significant and the advantage of the proposed method is compatibility with different criteria and providing sustainability results in different ways.
سرویس های شبکه های اجتماعی دیجیتال همان شبکه های اجتماعی هستند که مردم به اصطلاح عامیانه از این واژه استفاده می کنند. پلتفرم های رسانه های اجتماعی و وب سایت هایی که انتقال دانش از طریق شبکه های اجتماعی را امکان پذیر می کنند، ابزارهای دیجیتالی هستند که برای ساخت شبکه های اجتماعی و توسعه آنها طراحی شده اند. علاقه و استفاده زیاد از شبکه های اجتماعی این محیط ها را برای فعالیت های مختلف از جمله اقتصادی، فرهنگی، سیاسی و ... مهیا کرده است. رهبران رای یکی از مهمترین مواردی هستند که در این محیط ها تأثیر زیادی بر سایر کاربران دارند. رهبران رای در شبکه های اجتماعی سودمند هستند و ما می توانیم با شناسایی آنها از توانمندی و نفوذ آنها استفاده کنیم. در این مقاله، ما رهبران رای را با استفاده از الگوریتم بهینه سازی گرگ خاکستری انتخاب کرده ایم. این روش سلسله مراتب رهبری و سازوکار شکار گرگهای خاکستری را در طبیعت تقلید می کند و شامل 3 مرحله اصلی شکاریعنی جستجوی طعمه، محاصره طعمه و حمله به طعمه است. بر اساس بررسی ها و نتایج حاصله، تعداد رهبران واقعی رای تشخیص داده شده توسط این الگوریتم قابل توجه است و مزیت روش پیشنهادی سازگاری با معیارهای مختلف و ارائه نتایج پایداری درروش های مختلف است.
[1] Zhi-chao Cheng, Tian-chao Guo, The formation of social identity and self-identity based on knowledge contribution in virtual communities: An inductive route model, Computers in Human Behavior 43 (2015) 229-241.
[2] Giacomo Zanello, Xiaolan Fu, Pierre Mohnen, Marc Ventresca, The creation and diffusion of innovation in developing countries: a systematic literature review, Journal of Economic Surveys 30 (2016) 884-912.
[3] R. Dye, The buzz on buzz. harvard business review, Journal of Occupational and Environmental Medicine, 2000.
[4] E. Katz, P. F. Lazarsfeld, E. Roper, Personal influence: The part played by people in the flow of mass communications, Routledge, 2017.
[5] Y. Zhao, G. Kou, Yi. Peng, Y. Chen, Understanding influence power of opinion leaders in e-commerce networks: An opinion dynamics theory perspective, Information Sciences 426 (2018) 131-147.
[6] E. M. Rogers, D. G. Cartano, Methods of measuring opinion leadership, Public Opinion Quarterly 13 (1962) 435-441.
[7] T. W Valente, Patchareeya Pumpuang, Identifying opinion leaders to promote behavior change, Health Education and Behavior 34 (2007) 881-896.
[8] M. Afshar, M. Asadpour, Opinion formation by informed agents, Journal of Artificial Societies and Social Simulation 13 (2010) 14-22.
[9] L. Jain, R. Katarya, Sh. Sachdeva, Opinion leader detection using whale optimization algorithm in online social network, Expert Systems with Applications 142 (2020) 113-126.
[10] M. Taddicken, The Peoples Choice, How the Voter Makes Up His Mind in a Presidential Campaign, 25-36 Springer, 2016.
[11] J. M. Kleinberg, Authoritative sources in a hyperlinked environment, Journal of the ACM (JACM), 46(5):604{632, 1999.
[12] L. Jain, R. Katarya, Discover opinion leader in online social network using firefly algorithm, Expert Systems with Applications 122 (2019) 1-15.
[13] X. Song, Yun Chi, Koji Hino, Belle Tseng, Identifying opinion leaders in the blogosphere, Proceedings of the sixteenth ACM conference on Conference on information and knowledge management 971-974. ACM, 2019 .
[14] X. Yu, X. Wei, X. Lin, Algorithms of bbs opinion leader mining based on sentiment analysis. International Conference on Web Information Systems and Mining, pages 360-369. Springer.
[15] L. C. Freeman, Centrality in social networks conceptual clarification, Social networks 1 (1978) 15-239.
[16] F. Bodendorf, C. Kaiser, Detecting opinion leaders and trends in online social networks, Proceedings of the 2nd ACM workshop on Social web search and mining, Pades 65-68. ACM.
[17] N. Matsumura, Y. Ohsawa, M. Ishizuka, Mining and characterizing opinion leaders from threaded online discussions, Proceedings of the 6th International Conference on Knowledge-Based Intelligent Engineering Systems and Allied Technologies, Pages 1267-1270.
[18] Q. Miao, Sh. Zhang, Y. Meng, H. Yu, Domain-sensitive opinion leader mining from online review communities, Proceedings of the 22nd International Conference on World Wide Web, Pages 187-188. ACM.
[19] R. Vander Merwe, G. Heerden, Finding and utilizing opinion leaders: Social networks and the power of relationships, South African Journal of Business Management 40 (2009) 65-76.
[20] S. Al-Oufi, H. Nam Kim, A. El Saddik, A group trust metric for identifying people of trust in online social networks, Expert Systems with Applications 39 (2012) 13173-13181.
[21] S. Mohammad Aghdam, N. Jafari Navimipour, Opinion leaders selection in the social networks based on trust relationships propagation, Karbala International Journal of Modern Science 2 (2016) 88-97.
[22] N. Ma, Y. Liu, Superedgerank algorithm and its application in identifying opinion leader of online public opinion supernetwork, Expert Systems with Applications 41 (2014) 1357-1368.
[23] W. Cascio, S. Shurygailo, E-leadership and virtual teams organizational dynamics, Expert Systems with Applications 31 (2003) 362-376.
[24] Y. Seog Kim, V. Loc Tran, Assessing the ripple effects of online opinion leaders with trust and distrust metrics, Expert Systems with applications 40 (2013) 3500-3511.
[25] G. Sun, Sh. Bin, A new opinion leaders detecting algorithm in multi-relationship online social networks, Multimedia Tools and Applications 77 (2018) 4295-4307.
[26] AH. BorhaniAlamdari, M. Sharifi, DSolving a Joint Availability-Redundancy Optimization Model with Multi-State Components with Meta-Heuristic, International Journal of Industrial Mathematics 12 (2020) 59-70.
[27] S. A. Mirjalili, S. M. Mirjalili, A. Lewis, Grey wolf optimizer, Advances in engineering software 69 (2014) 46-61.
[28] H. Shayanfar, F. Soleimanian Gharehchopogh, Farmland fertility: A new metaheuristic algorithm for solving continuous optimization problems, Applied Soft Computing 71 (2018) 728-746.
[29] M. Y. Cheng, D. Prayogo, Symbiotic organisms search: a new metaheuristic optimization algorithm, Computers and Structures 139 (2014) 98-112.
[30] F. Soleimanian Gharehchopogh, H. Shayanfar, H. Gholizadeh, A comprehensive survey on symbiotic organisms search algorithms, Artificial Intelligence Review 13 (2019) 1-48.
| [31] F. | Soleimanian | Gharehchopogh, | H. | |
| Gholizadeh, | A comprehensive survey: | |||
| Whale | optimization | algorithm | and | its |
| applications, | Swarm and Evolutionary |
Computation 48 (2019) 1-24.
[32] S. A.li Mirjalili, A. Lewis, The whale optimization algorithm, Advances in engineering software 95 (2016) 51-67.
[33] L. David Mech, Alpha status, dominance, and division of labor in wolf packs, Canadian Journal of Zoology 77 (1999) 1196-1203.
[34] C. Muro, R. Escobedo, L. Spector, RP. Coppinger, Wolf-pack (canis lupus) hunting strategies emerge from simple rules in computational simulations, Behavioural processes 88 (2011) 192-197.
[35] Extended epinions,. http://www.trustlet.org/datasets/ extendedepinions/userrating.txt.
[36] F. Bodendorf, C. Kaiser, Detecting opinion leaders and trends in online social networks, Proceedings of the 2nd ACM workshop on Social web search and mining, pages 65{68. ACM.
37] F. Li, T. C. Du, Who is talking an ontology-based opinion leader identification framework for word-of-mouth marketing in online social blogs, Decision Support Systems 51 (2011) 190-197
