روشی ترکیبی برای شناسایی جوامع مبتنی بر تعاملات کاربران، توپولوژی شبکه و کاوش الگوی تکرارشونده

[1] Li, XiaoMing, Guangquan Xu, and Minghu Tang, "Community detection for multi-layer social network based on local random walk", Journal of Visual Communication and Image Representation. 57 (2018): 91-98.

[2] Dabaghi-Zarandi, Fahimeh, and Parsa KamaliPour, "Community detection in complex network based on an improved random algorithm using local and global network information", Journal of Network and Computer Applications. 206 (2022): 103492.

[3] Aggarwal, Charu C,An introduction to social network data analytics,Springer, 2011.

[4] Moscato, Vincenzo, and Giancarlo Sperlì, "A survey about community detection over On-line Social and Heterogeneous Information Networks", Knowledge-Based Systems. 224 (2021): 107112.

[5] Luo, Linbo, Kexin Liu, Bin Guo, and Jianfeng Ma, "User interaction-oriented community detection based on cascading analysis", Information Sciences. 510 (2020): 70-88.

[6] گلکار، ایمان و  مرجان کائدی. " ارائه مدلی برای تخمین میزان برون‌گرایی اعضای شبکه اجتماعی با استفاده از اطلاعات ساختار گراف". نشریه مدل‌سازی در مهندسی 13، 43، (1394): 91-106. (inPersian)

[7] Wilson, Christo, Alessandra Sala, Krishna P. N. Puttaswamy, and Ben Y. Zhao, "Beyond Social Graphs", ACM Transactions on the Web. 6 (2012): 1-31.

[8] Ahmed, Cherry, and Abeer ElKorany, "Enhancing link prediction in Twitter using semantic user attributes".Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2015, 1155-1161, 2015.

[9] O’Riordan, Sheila, Joseph Feller, and Tadhg Nagle, "A categorisation framework for a feature-level analysis of social network sites", Journal of Decision Systems. 25 (2016): 244-262.

[10] Moosavi, Seyed Ahmad, and Mehrdad Jalali, "Community detection in online social networks using actions of users".2014 Iranian Conference on Intelligent Systems (ICIS), 1-7, (IEEE), 2014.

[11] Dev, Himel, Mohammed Eunus Ali, and Tanzima Hashem, "User interaction based community detection in online social networks".Database Systems for Advanced Applications: 19th International Conference, DASFAA 2014, Bali, Indonesia, April 21-24, 2014. Proceedings, Part II 19, 296-310, (Springer), 2014.

[12] Vathi, Eleni, Georgios Siolas, Andreas Stafylopatis, Ngoc-Thanh Nguyen, Manuel Núñez, and Bogdan Trawiński, "Mining and categorizing interesting topics in Twitter communities", Journal of Intelligent & Fuzzy Systems. 32 (2017): 1265-1275.

[13] Moosavi, Seyed Ahmad, Mehrdad Jalali, Negin Misaghian, Shahaboddin Shamshirband, and Mohammad Hossein Anisi, "Community detection in social networks using user frequent pattern mining", Knowledge and Information Systems. 51 (2017): 159-186.

[14] Wang, Yang, Zengru Di, and Ying Fan, "Identifying and characterizing nodes important to community structure using the spectrum of the graph", Public Library of Science. 6 (2011): e27418.

[15] Ai, Jun, Tao He, Zhan Su, and Lihui Shang, "Identifying influential nodes in complex networks based on spreading probability", Chaos, Solitons & Fractals. 164 (2022): 112627.

[16] Xia, Yingjie, Xiaolong Ren, Zhengchao Peng, Jianlin Zhang, and Li She, "Effectively identifying the influential spreaders in large-scale social networks", Multimedia Tools and Applications. 75 (2016): 8829-8841.

[17] Hansen, Derek, Ben Shneiderman, and Marc A Smith,Analyzing Social Media Networks with NodeXL: Insights from a Connected World (Second Edition),(Morgan Kaufmann 2020), pp.Chapter 3.

[18] Ahajjam, Sara, Mohamed El Haddad, and Hassan Badir, "A new scalable leader-community detection approach for community detection in social networks", Social Networks. 54 (2018): 41-49.

[19] Zhong, Lin-Feng, Ming-Sheng Shang, Xiao-Long Chen, and Shi-Ming Cai, "Identifying the influential nodes via eigen-centrality from the differences and similarities of structure", Physica A: Statistical Mechanics and its Applications. 510 (2018): 77-82.

[20] Goyal, Amit, Francesco Bonchi, and Laks VS Lakshmanan, "Discovering leaders from community actions".Proceedings of the 17th ACM conference on Information and knowledge management, 499-508, 2008.

[21] Lu, Dongyuan, Qiudan Li, and Stephen Shaoyi Liao, "A graph-based action network framework to identify prestigious members through member's prestige evolution", Decision Support Systems. 53 (2012): 44-54.

[22] Bamakan, Seyed Mojtaba Hosseini, Ildar Nurgaliev, and Qiang Qu, "Opinion leader detection: A methodological review", Expert Systems with Applications. 115 (2019): 200-222.

[23] Kolahkaj, Maral, Ali Harounabadi, Alireza Nikravanshalmani, and Rahim Chinipardaz, "A hybrid context-aware approach for e-tourism package recommendation based on asymmetric similarity measurement and sequential pattern mining", Electronic Commerce Research and Applications. 42 (2020): 100978.

[24] Martínez, Víctor, Fernando Berzal, and Juan-Carlos Cubero, "A Survey of Link Prediction in Complex Networks", ACM Computing Surveys. 49 (2016): 1-33.

[25] صالحی، سید محمدمهدی و  علی‌اکبر پویان. " مروری بر روش‌های مدل‌سازی هم‌پوشانی در الگوریتم‌های انجمن‌یابی شبکه‌های اجتماعی". نشریه مدل‌سازی در مهندسی 17، 56 (1398): 247- 256. (inPersian)

[26] Paul, Amit, and Animesh Dutta, "Community detection using Local Group Assimilation", Expert Systems with Applications. 206 (2022): 117794.

[27] Tumiran, Siti Aisyah, and Bellie Sivakumar, "Community structure concept for catchment classification: A modularity density-based edge betweenness (MDEB) method", Ecological Indicators. 124 (2021): 107346.

[28] Arab, Mohsen, and Mohsen Afsharchi, "Community detection in social networks using hybrid merging of sub-communities", Journal of Network and Computer Applications. 40 (2014): 73-84.

[29] Dugué, Nicolas, and Anthony Perez, "Direction matters in complex networks: A theoretical and applied study for greedy modularity optimization", Physica A: Statistical Mechanics and its Applications. 603 (2022): 127798.

[30] Berahmand, Kamal, and Asgarali Bouyer, "A Link-Based Similarity for Improving Community Detection Based on Label Propagation Algorithm", Journal of Systems Science and Complexity. 32 (2018): 737-758.

 [31] Wu, Wenhui, Sam Kwong, Yu Zhou, Yuheng Jia, and Wei Gao, "Nonnegative matrix factorization with mixed hypergraph regularization for community detection", Information Sciences. 435 (2018): 263-281.

[32] Yakoubi, Zied, and Rushed Kanawati, "LICOD: A Leader-driven algorithm for community detection in complex networks", Vietnam Journal of Computer Science. 1 (2014): 241-256.

[33] Li, Wei, Ce Huang, Miao Wang, and Xi Chen, "Stepping community detection algorithm based on label propagation and similarity", Physica A: Statistical Mechanics and its Applications. 472 (2017): 145-155.

[34] Srilatha, Pulipati, and Ramakrishnan Manjula, "Similarity index based link prediction algorithms in social networks: A survey", Journal of Telecommunications and Information Technology. (2016): 87-94.

[35] Belfin, RV, and Piotr Bródka, "Overlapping community detection using superior seed set selection in social networks", Computers & Electrical Engineering. 70 (2018): 1074-1083.

[36] Pan, Xiaohui, Guiqiong Xu, Bing Wang, and Tao Zhang, "A Novel Community Detection Algorithm Based on Local Similarity of Clustering Coefficient in Social Networks", IEEE Access. 7 (2019): 121586-121598.

[37] Mishra, Sneha, Shashank Sheshar Singh, Shivansh Mishra, and Bhaskar Biswas, "TCD2: Tree-based community detection in dynamic social networks", Expert Systems with Applications. 169 (2021): 114493.

[38] Helal, Nivin A., Rasha M. Ismail, Nagwa L. Badr, and Mostafa G. M. Mostafa, "Leader‐based community detection algorithm for social networks", WIREs Data Mining and Knowledge Discovery. 7 (2017).

[39] Yang, Chen, Lei Liu, Li Chen, and Ben Niu, "A novel friend recommendation service based on interaction information mining".2017 International Conference on Service Systems and Service Management, 1-5, (IEEE), 2017.

[40] Lim, Kwan Hui, and Amitava Datta, "An interaction-based approach to detecting highly interactive Twitter communities using tweeting links", Web Intelligence. 14 (2016): 1-15.

[41] Bonacich, Phillip, "Power and centrality: A family of measures", American journal of sociology. 92 (1987): 1170-1182.

[42] Zaki, Mohammed Javeed, "Scalable algorithms for association mining", IEEE transactions on knowledge and data engineering. 12 (2000): 372-390.

[43] Telikani, Akbar, Amir H. Gandomi, and Asadollah Shahbahrami, "A survey of evolutionary computation for association rule mining", Information Sciences. 524 (2020): 318-352.

[44] Luo, Wenjian, Nannan Lu, Li Ni, Wenjie Zhu, and Weiping Ding, "Local community detection by the nearest nodes with greater centrality", Information Sciences. 517 (2020): 377-392.

[45]Malliaros, Fragkiskos D, and Michalis Vazirgiannis, "Clustering and community detection in directed networks: A survey", Physics reports. 533 (2013): 95-142.

[46] De Domenico, Manlio, Antonio Lima, Paul Mougel, and Mirco Musolesi, "The anatomy of a scientific rumor", Scientific reports. 3 (2013): 2980.

 [47] Platform, Stanford Network Analysis, and (SNAP)  higgs-twitter (Accessed February 18, 2023) (2015 ) http://snap.stanford.edu/data/higgs-twitter.html

[48] Tan, Chenhao, Jie Tang, Jimeng Sun, Quan Lin, and Fengjiao Wang, "Social action tracking via noise tolerant time-varying factor graphs".Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining, 1049-1058, 2010.

[49] (ArnetMiner), AMiner  Flickr-large Accessed February 18, 2023 (2006) https://www.aminer.cn/data-sna#Flickr large

[50] Lancichinetti, Andrea, Santo Fortunato, and János Kertész, "Detecting the overlapping and hierarchical community structure in complex networks", New journal of physics. 11 (2009): 033015.

[51] Sun, Peng Gang, Xunlian Wu, Yining Quan, and Qiguang Miao, "Influence percolation method for overlapping community detection", Physica A: Statistical Mechanics and its Applications. 596 (2022): 127103.

[52] Singh, Dipika, and Rakhi Garg, "NI-Louvain: A novel algorithm to detect overlapping communities with influence analysis", Journal of King Saud University - Computer and Information Sciences. 34 (2022): 7765-7774.