Clarifying the evolution structure of public opinion induced and spread by fragmentation in college students’ network circle group is the key to understanding college students’ online social psychological demands, grasping the development trend of public opinion, and designing targeted public opinion governance strategies. On the basis of identifying the key variables in the process of public opinion communication, DEMATEL-ISM model is used to explore the attribute positioning, relative importance level and hierarchical association mechanism of ante-variable and result variable, and then the governance strategies for fragment disordering public opinion in network circle groups of college students is designed. According to the study, exogenous stimuli, the uniqueness of discourse system, the number of spectacular texts and micro-narrative mode constituted the deep-rooted causes of fragment disordering public opinion. The unique situational and information attributes of network circle groups often become an important “booster” of disordered public opinion. The topic deviation is often accompanied with the formation of negative emotions. The corresponding public opinion governance strategies are sought from the aspects of shaping the network environment, adjusting the operation mechanism of the network circle group, improving the efficiency of using fragmented information, and optimizing the human resources of colleges.
References
[1]
Sullivan, R., Tysick, C.A., Pilawski, B., Strause, S.S., van Putten, C. and Whitley-Grassi, N. (2014) Tools of Engagement Project (TOEP): Online Professional Development through Structured Inquiry and a Virtual Community. In: Sullivan, R., Tysick, C.A., Pilawski, B., Strause, S.S., van Putten, C. and Whitley-Grassi, N., Eds., Innovations in Higher EducationTeaching and Learning, Emerald Group Publishing Limited, 377-392. https://doi.org/10.1108/s2055-364120140000001019
[2]
Ye, P. and Liu, L. (2021) Factors Influencing College Students’ Behaviours of Spreading Internet Public Opinions on Emergencies in Universities. Information Discovery and Delivery, 50, 75-86. https://doi.org/10.1108/idd-10-2020-0126
[3]
Smith, T. and Lambert, R. (2014) A Systematic Review Investigating the Use of Twitter and Facebook in University-Based Healthcare Education. Health Education, 114, 347-366. https://doi.org/10.1108/he-07-2013-0030
[4]
Nerurkar, P., Chandane, M. and Bhirud, S. (2019) Understanding Attribute and Social Circle Correlation in Social Networks. Turkish Journal of Electrical Engineering & Computer Sciences, 27, 1228-1242. https://doi.org/10.3906/elk-1806-91
[5]
Nian, F. and Liu, X. (2021) Friend Circles Network: Formation and the Law of News Dissemination. Applied Intelligence, 52, 889-902. https://doi.org/10.1007/s10489-021-02398-z
[6]
Han Mo, P.K., Ma, L., Li, J., Xie, L., Liu, X., Jiang, H., et al. (2024) Communication in Social Networking Sites on Offline and Online Social Support and Life Satisfaction among University Students: Tie Strength Matters. Journal of Adolescent Health, 74, 971-979. https://doi.org/10.1016/j.jadohealth.2023.10.030
[7]
Feng, J., Hu, B., Sun, J., Zhang, J., Wang, W. and Cui, G. (2021) Identifying Fragmented Reading and Evaluating Its Influence on Cognition Based on Single Trial Electroencephalogram. Frontiers in Human Neuroscience, 15, Article 753735. https://doi.org/10.3389/fnhum.2021.753735
[8]
Liu, W., Huang, H., Saleem, A. and Zhao, Z. (2022) The Effects of University Students’ Fragmented Reading on Cognitive Development in the New Media Age: Evidence from Chinese Higher Education. PeerJ, 10, e13861. https://doi.org/10.7717/peerj.13861
[9]
Xie, W. (2019) An Analysis of Fragmented Reading and Its Social Impact on College Students in the Era of New Media. Journal of Contemporary Educational Research, 3, 33-37. https://doi.org/10.26689/jcer.v3i3.693
[10]
Liu, J., Wang, S., Wang, Z. and Chen, S. (2024) Research on Online Public Opinion Dissemination and Emergency Countermeasures of Food Safety in Universities—Take the Rat Head and Duck Neck Incident in China as an Example. Frontiers in Public Health, 11, Article 1346577. https://doi.org/10.3389/fpubh.2023.1346577
[11]
Xu, B. and Liu, Y. (2022) The Role of Big Data in Network Public Opinion within the Colleges and Universities. Soft Computing, 26, 10853-10862. https://doi.org/10.1007/s00500-022-07082-z
[12]
Alonso, J., Paredes, R. and Rosso, P. (2016) Feature Representation for Social Circles Detection Using Mac. Neural Computing and Applications, 28, 2395-2402. https://doi.org/10.1007/s00521-016-2222-y
[13]
Hill, A. and Peuker, S. (2023) Expanding Students’ Social Networks via Optimized Team Assignments. Annals of Operations Research, 332, 1107-1131. https://doi.org/10.1007/s10479-023-05492-2
[14]
Xia, H., Yan, Z. and Bowen, A. (2016) The Mechanism and Influencing Factors of Herding Effect of College Students’ Network Public Opinion. The Anthropologist, 23, 226-230. https://doi.org/10.1080/09720073.2016.11891945
[15]
Wang, S.Q., Li, T.S., Shen, X.F. and Zhao, H.Y. (2024) China University Online Public Opinion Risk Dataset. IEEE Access, 12, 55225-55233. https://doi.org/10.1109/ACCESS.2024.3389974
[16]
Zhu, H., Ma, J. and Li, S. (2019) Effects of Online and Offline Interaction on Rumor Propagation in Activity-Driven Networks. Physica A: Statistical Mechanics and Its Applications, 525, 1124-1135. https://doi.org/10.1016/j.physa.2019.04.006
[17]
Yu, B. and Leung, Y.W. (2023) Establishing Ties or Strengthening Friendships? Students’ Use of Online Social Networks in Intercultural Friendship Development. Information Technology & People, 37, 815-834. https://doi.org/10.1108/itp-01-2022-0035
[18]
Hou, Y., Zhang, D., Gan, X. and Hu, Y. (2022) Group Polarization Calls for Group-Level Brain Communication. NeuroImage, 264, Article 119739. https://doi.org/10.1016/j.neuroimage.2022.119739
[19]
Del Vicario, M., Vivaldo, G., Bessi, A., Zollo, F., Scala, A., Caldarelli, G., et al. (2016) Echo Chambers: Emotional Contagion and Group Polarization on Facebook. Scientific Reports, 6, Article No. 37825. https://doi.org/10.1038/srep37825
[20]
He, M., Ma, C. and Wang, R. (2022) A Data-Driven Approach for University Public Opinion Analysis and Its Applications. Applied Sciences, 12, Article 9136. https://doi.org/10.3390/app12189136
[21]
Nan, F., Suo, Y., Jia, X., Wu, Y. and Shan, S. (2018) Real-Time Monitoring of Smart Campus and Construction of Weibo Public Opinion Platform. IEEE Access, 6, 76502-76515. https://doi.org/10.1109/access.2018.2883799
[22]
Wang, C., Hao, C. and Guan, X. (2020) Hierarchical and Overlapping Social Circle Identification in Ego Networks Based on Link Clustering. Neurocomputing, 381, 322-335. https://doi.org/10.1016/j.neucom.2019.11.080
[23]
Agarwal, V. and Bharadwaj, K.K. (2015) Predicting the Dynamics of Social Circles in Ego Networks Using Pattern Analysis and GA K‐Means Clustering. WIREs Data Mining and Knowledge Discovery, 5, 113-141. https://doi.org/10.1002/widm.1150
[24]
Pan, W. and Lan, X. (2009) Building a Virtual Community Platform for Subject Information Services at Shanghai Jiao Tong University Library. The Electronic Library, 27, 271-282. https://doi.org/10.1108/02640470910947610
[25]
Alemany, J., Del Val, E. and García-Fornes, A.M. (2021) “Who Should I Grant Access to My Post?”: Identifying the Most Suitable Privacy Decisions on Online Social Networks. Internet Research, 31, 1290-1317. https://doi.org/10.1108/intr-03-2020-0128
[26]
Zhi, H. and Zhang, D. (2022) Effects of Professional Virtual Community Attributes and Flow Experience on Information Sharing among Chinese Young Netizens: A Fuzzy-Set QCA. Psychology Research and Behavior Management, 15, 3497-3511. https://doi.org/10.2147/prbm.s387166
[27]
Doshi, P., Nigam, P. and Rishi, B. (2023) System Quality Features and Continuous Usage Intention of Social Network Users: A Multi-Group Analysis with Gender. Journal of Systems and Information Technology, 25, 480-501. https://doi.org/10.1108/jsit-07-2022-0164
[28]
Kang, H., Han, J. and Kwon, G.H. (2018) An Integrated Success Factor Model of Professional Virtual Communities: Incorporation of the Operators, Members, and Life Cycle Perspectives. International Journal of Human-Computer Interaction, 35, 1312-1330. https://doi.org/10.1080/10447318.2018.1519977
[29]
Qutab, S., Iqbal, A., Ullah, F.S., Siddique, N. and Khan, M.A. (2022) Role of Virtual Communities of Practice (VCoP) in Continuous Professional Development of Librarians: A Case of Yahoo Mailing Group from Pakistan. Library Management, 43, 317-333. https://doi.org/10.1108/lm-02-2021-0017
[30]
Li, D. (2023) The Challenge and the Countermeasure of “Information Cocoon” to the Integration of Excellent Regional Culture into Ideological and Political Education in Colleges and Universities. International Journal of Education and Humanities, 7, 76-80. https://doi.org/10.54097/ijeh.v7i3.6004
[31]
Turner, M.A. and Smaldino, P.E. (2018) Paths to Polarization: How Extreme Views, Miscommunication, and Random Chance Drive Opinion Dynamics. Complexity, 2018, Article 2740959. https://doi.org/10.1155/2018/2740959
[32]
Sankaran, K. and Demangeot, C. (2017) Conceptualizing Virtual Communities as Enablers of Community-Based Entrepreneurship and Resilience. Journal of Enterprising Communities: People and Places in the Global Economy, 11, 78-94. https://doi.org/10.1108/jec-02-2015-0017
[33]
Delgado, P. and Salmerón, L. (2021) The Inattentive on-Screen Reading: Reading Medium Affects Attention and Reading Comprehension under Time Pressure. Learning and Instruction, 71, Article 101396. https://doi.org/10.1016/j.learninstruc.2020.101396
[34]
Meel, P. and Vishwakarma, D.K. (2020) Fake News, Rumor, Information Pollution in Social Media and Web: A Contemporary Survey of State-of-the-Arts, Challenges and Opportunities. Expert Systems with Applications, 153, Article 112986. https://doi.org/10.1016/j.eswa.2019.112986
[35]
Zhang, Y., Lian, J., Li, R. and Duan, H. (2023) Research on the Evolution of Netizens’ Comment Focus in University Online Public Opinion: KTF-BTM Topic Model with Topic-Temporal-Focus Framework. Frontiers in Physics, 11, Article 1251386. https://doi.org/10.3389/fphy.2023.1251386
[36]
Lv, Z. (2022) Prediction of the Forwarding Volume of Campus Microblog Public Opinion Emergencies Using Neural Network. Mobile Information Systems, 2022, Article 3064266. https://doi.org/10.1155/2022/3064266
[37]
Chiu, C., Fu, C., Lin, W. and Chen, C. (2019) The Central Roles of Embeddedness and Engagement in Virtual Communities. Online Information Review, 43, 531-550. https://doi.org/10.1108/oir-10-2017-0304
[38]
Assimakopoulos, C., Antoniadis, I., Kayas, O.G. and Dvizac, D. (2017) Effective Social Media Marketing Strategy: Facebook as an Opportunity for Universities. International Journal of Retail & Distribution Management, 45, 532-549. https://doi.org/10.1108/ijrdm-11-2016-0211
[39]
Hu, Z. (2023) Digging Deeper into Responsibility: An Investigation of Responses to Online Help-Request Marketing Campaigns in Social Networking Groups. Information Technology & People, 37, 677-699. https://doi.org/10.1108/itp-03-2022-0170
[40]
Chai, J. and Ye, J. (2024) A Social Network Analysis of College Students’ Online Learning during the Epidemic Era: A Triadic Reciprocal Determinism Perspective. Heliyon, 10, e28107. https://doi.org/10.1016/j.heliyon.2024.e28107
[41]
Lai, H., Chen, C. and Chang, Y. (2014) Determinants of Knowledge Seeking in Professional Virtual Communities. Behaviour & Information Technology, 33, 522-535. https://doi.org/10.1080/0144929x.2013.864709
[42]
Du, Y. and Shen, X. (2023) Group Hierarchical DEMATEL Method for Reaching Consensus. Computers & Industrial Engineering, 175, Article 108842. https://doi.org/10.1016/j.cie.2022.108842
[43]
Bagherian, A., Gershon, M., Kumar, S. and Kumar Mishra, M. (2024) Analyzing the Relationship between Digitalization and Energy Sustainability: A Comprehensive ISM-MICMAC and DEMATEL Approach. Expert Systems with Applications, 236, Article 121193. https://doi.org/10.1016/j.eswa.2023.121193
[44]
Mishra, R. (2020) An Analysis of Factors Influencing Omnichannel Retailing Adoption Using ISM-DEMATEL Approach: An Indian Perspective. International Journal of Retail & Distribution Management, 49, 550-576. https://doi.org/10.1108/ijrdm-03-2020-0108
[45]
López, M., Sicilia, M. and Verlegh, P.W.J. (2021) How to Motivate Opinion Leaders to Spread e-WoM on Social Media: Monetary vs Non-Monetary Incentives. Journal of Research in Interactive Marketing, 16, 154-171. https://doi.org/10.1108/jrim-03-2020-0059
[46]
Kim, Y. and Kim, B. (2021) Effects of Young Adults’ Smartphone Use for Social Media on Communication Network Heterogeneity, Social Capital and Civic Engagement. Online Information Review, 46, 616-638. https://doi.org/10.1108/oir-08-2020-0332
[47]
Kazeem Kayode, B., Zamzami, I.F. and Olowolayemo, A. (2012) Students’ Orientation Towards Interpersonal Communication in Online Social Networking Sites. Multicultural Education & Technology Journal, 6, 36-44. https://doi.org/10.1108/17504971211216300
[48]
Song, W., Zhu, Y. and Zhao, Q. (2020) Analyzing Barriers for Adopting Sustainable Online Consumption: A Rough Hierarchical DEMATEL Method. Computers & Industrial Engineering, 140, Article 106279. https://doi.org/10.1016/j.cie.2020.106279
