Machine learning algorithms for social media analysis: A survey

Automated Detection of Adverse Drug Reactions from Social Media Posts with Machine Learning

Alimova, I., & Tutubalina, E. V. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-73013-4_1 · Cited by 46

Business Intelligence Model to Analyze Social Media Information

Kurnia, P. F., & Suharjito, S. (2018) · Procedia Computer Science · doi:10.1016/j.procs.2018.08.144 · Cited by 46

Mining social network users opinions’ to aid buyers’ shopping decisions

D’Avanzo, E., & Pilato, G. (2014) · Computers in Human Behavior · doi:10.1016/j.chb.2014.11.081 · Cited by 45

NeedFull – a Tweet Analysis Platform to Study Human Needs During the COVID-19 Pandemic in New York State

Long, Z., Alharthi, R., & Saddik, A. E. (2020) · IEEE Access · doi:10.1109/access.2020.3011123 · Cited by 45

Creative social media use and political participation in young people: The moderation and mediation role of online political expression

Zhu, A. Y. F., Chan, A. L. S., & Chou, K. (2019) · Journal of Adolescence · doi:10.1016/j.adolescence.2019.10.010 · Cited by 44

Discovering missing me edges across social networks

Buccafurri, F., Lax, G., Nocera, A., & Domenico Ursino, A. (2015) · Information Sciences · doi:10.1016/j.ins.2015.05.014 · Cited by 44

Sentiment community detection: exploring sentiments and relationships in social networks

Wang, D. Y., Li, J., Xu, K. S. J., & Wu, Y. (2016) · Electronic Commerce Research · doi:10.1007/s10660-016-9233-8 · Cited by 44

An enhanced trust prediction strategy for online social networks using probabilistic reputation features

Raj, E. D., & Babu, L. D. D. (2016) · Neurocomputing · doi:10.1016/j.neucom.2016.09.036 · Cited by 44

When crowdsourcing meets mobile sensing: a social network perspective

Chen, P., Cheng, S., Ting, P., Lien, C.-W., & Chu, F.-J. (2015) · IEEE Communications Magazine · doi:10.1109/mcom.2015.7295478 · Cited by 43

Detecting users’ anomalous emotion using social media for business intelligence

Sun, X. N., Zhang, C., Li, G., Sun, D. W., Ren, F., Zomaya, A. Y., & Ranjan, R. K. (2017) · Journal of Computational Science · doi:10.1016/j.jocs.2017.05.029 · Cited by 43

On Textual Analysis and Machine Learning for Cyberstalking Detection

Frommholz, I., Al‐Khateeb, H., Potthast, M., Ghasem, Z., Shukla, M., & Short, E. (2016) · Datenbank-Spektrum · doi:10.1007/s13222-016-0221-x · Cited by 41

A Social-aware online short-text feature selection technique for social media

Tommasel, A., & Godoy, D. L. (2017) · Information Fusion · doi:10.1016/j.inffus.2017.05.003 · Cited by 41

Rumor Detection Using Machine Learning Techniques on Social Media

Kumar, A., & Sangwan, S. R. (2018) · Lecture notes in networks and systems · doi:10.1007/978-981-13-2354-6_23 · Cited by 41

Elementary modelling and behavioural analysis for emergency evacuations using social media

Fry, J. M., & Binner, J. M. (2015) · European Journal of Operational Research · doi:10.1016/j.ejor.2015.05.049 · Cited by 40

Root Cause Analysis of Network Failures Using Machine Learning and Summarization Techniques

Gonzalez, J. M. N., Jiménez, J., López, J. C. D., & G., H. A. P. (2017) · IEEE Communications Magazine · doi:10.1109/mcom.2017.1700066 · Cited by 40

International Conference on Innovative Computing and Communications

Khanna, A. K., Gupta, D. K., Bhattacharyya, S., Snåšel, V., Platoš, J., & Hassanien, A. E. (2020) · Advances in intelligent systems and computing · doi:10.1007/978-981-15-1286-5 · Cited by 40

Evaluation of Performance Measures for Classifiers ComparisonPreprint

Labatut, V., & Cherifi, H. (2011) · arXiv (Cornell University) · doi:10.48550/arxiv.1112.4133 · Cited by 39

Crowdsensing the speaker count in the wild: implications and applications

Xu, C., Li, S., Zhang, Y., Miluzzo, E., & Chen, Y.-F. (2014) · IEEE Communications Magazine · doi:10.1109/mcom.2014.6917408 · Cited by 39

Learning Person-Specific Representations From Faces in the Wild

Chiachia, G., Falcão, A. X., Pinto, N., Rocha, A. D. R., & Cox, D. (2014) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2014.2359543 · Cited by 37

Cloud computing service for knowledge assessment and studies recommendation in crowdsourcing and collaborative learning environments based on social network analysis

Stantchev, V., González, L. P., & Tamm, G. (2015) · Computers in Human Behavior · doi:10.1016/j.chb.2014.11.092 · Cited by 35

Online social construction of Taiwan's rural image: Comparison between Taiwanese self-representation and Chinese perception

Sun, Y., Liang, C., & Chang, C. (2019) · Tourism Management · doi:10.1016/j.tourman.2019.103968 · Cited by 35

#(Me)too much? The role of sexualizing online media in adolescents’ resistance towards the metoo‐movement and acceptance of rape myths

Maes, C., Schreurs, L., van Oosten, J. M. F., & Vandenbosch, L. (2019) · Journal of Adolescence · doi:10.1016/j.adolescence.2019.10.005 · Cited by 35

Solving Large Scale Learning Tasks. Challenges and Algorithms

Stolpe, M., Piatkowski, N., & Michaelis, S. (2016) · Lecture notes in computer science · doi:10.1007/978-3-319-41706-6 · Cited by 34

Network enforcement as denunciation endorsement? A critical study on legal enforcement in social media

Kasakowskij, T., Fürst, J., Fischer, J., & Fietkiewicz, K. J. (2019) · Telematics and Informatics · doi:10.1016/j.tele.2019.101317 · Cited by 33

Who are the spoilers in social media marketing? Incremental learning of latent semantics for social spam detection

Song, L., Lau, R. Y. K., Kwok, R. C.-W., Mirkovski, K., & Dou, W. (2016) · Electronic Commerce Research · doi:10.1007/s10660-016-9244-5 · Cited by 33

Designing a social-broadcasting-based business intelligence system

Rui, H., & Whinston, A. B. (2011) · ACM Transactions on Management Information Systems · doi:10.1145/2070710.2070713 · Cited by 32

Exploring negative peer communication of companies on social media and its impact on organization-public relationships

Qin, Y. S., & Men, L. R. (2019) · Public Relations Review · doi:10.1016/j.pubrev.2019.05.016 · Cited by 32

Sentiment Analysis of Law Enforcement Performance Using Support Vector Machine and K-Nearest Neighbor

Istia, S. S., & Purnomo, H. D. (2018) · International Conference on Information Technology, Information Systems and Electrical Engineering (ICITISEE) · doi:10.1109/icitisee.2018.8720969 · Cited by 32

Energetic voices on social media? Strategic Niche Management and Finnish Facebook debate on biogas and heat pumps

Rantala, S., Toikka, A., Pulkka, A., & Lyytimäki, J. M. (2019) · Energy Research & Social Science · doi:10.1016/j.erss.2019.101362 · Cited by 31

Narcissism, interactivity, community, and online revenge behavior: The moderating role of social presence among Jordanian consumers

Obeidat, Z. M., Algharabat, R., Alalwan, A. A., Xiao, S. H., Dwivedi, Y. K., & Rana, N. P. (2019) · Computers in Human Behavior · doi:10.1016/j.chb.2019.106170 · Cited by 30

Temporal and Geographic Patterns of Social Media Posts About an Emerging Suicide Game

Sumner, S. A., Galik, S., Mathieu, J., Ward, M., Kiley, T., Bartholow, B., Dingwall, A., & Mork, P. (2019) · Journal of Adolescent Health · doi:10.1016/j.jadohealth.2018.12.025 · Cited by 30

Detecting Breathing and Snoring Episodes Using a Wireless Tracheal Sensor—A Feasibility Study

Młyńczak, M., Migacz, E., Migacz, M., & Kukwa, W. (2016) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2016.2632976 · Cited by 29

Behavior-aware user response modeling in social media: Learning from diverse heterogeneous data

Chen, Z.-Y., Fan, Z.-P., & Sun, M. (2014) · European Journal of Operational Research · doi:10.1016/j.ejor.2014.09.008 · Cited by 28

A systematic literature review: What is the current stance towards weight stigmatization in social media platforms?

Wanniarachchi, V. U., Mathrani, A., Sušnjak, T., & Scogings, C. (2020) · Int. J. Hum. Comput. Stud. · doi:10.1016/j.ijhcs.2019.102371 · Cited by 28

A Quick Guide for Building a Successful Bioinformatics Community

Budd, A., Corpas, M., Brazas, M. D., Fuller, J. C., Goecks, J., Mulder, N., Michaut, M., Ouellette, B. F. F., Pawlik, A., & Blomberg, N. (2015) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1003972 · Cited by 27

Formal knowledge model for online social network forensics

Arshad, H., Jantan, A., Hoon, G. K., & Abiodun, I. O. (2019) · Computers & Security · doi:10.1016/j.cose.2019.101675 · Cited by 27

A Formal Machine–Learning Approach to Generating Human–Machine Interfaces From Task Models

Li, M., Wei, J., Zheng, X., & Bolton, M. L. (2017) · IEEE Transactions on Human-Machine Systems · doi:10.1109/thms.2017.2700630 · Cited by 27

Whether the weather will help us weather the COVID-19 pandemic: Using machine learning to measure twitter users’ perceptions

Gupta, M., Bansal, A., Jain, B., Rochelle, J., Oak, A., & Jalali, M. S. (2020) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2020.104340 · Cited by 26

A Unified Framework of Latent Feature Learning in Social Media

Yuan, Z., Sang, J., Xu, C., & Liu, Y. (2014) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2014.2322338 · Cited by 26

Efficient Vector Influence Clustering Coefficient Based Directed Community Detection Method

Deng, X., Zhai, J., Lv, T., & Yin, L. (2017) · IEEE Access · doi:10.1109/access.2017.2740962 · Cited by 24

The Relation between Destination Image and Social Media user Engagement – theoretical Approach

Stepaniuk, K. (2015) · Procedia - Social and Behavioral Sciences · doi:10.1016/j.sbspro.2015.11.459 · Cited by 23

Web video topics discovery and structuralization with social network

Cao, J., Zhang, Y., Ji, R., Xie, F., & Su, Y. (2015) · Neurocomputing · doi:10.1016/j.neucom.2014.10.103 · Cited by 20

Linguistic Dynamic Analysis of Traffic Flow Based on Social Media—A Case Study

Mo, H., Hao, X., Zheng, H., Liu, Z., & Wen, D. (2016) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2016.2530698 · Cited by 20

2007 International Conference on Information and Communication Technology

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The impact of the mere presence of social media share icons on product interest and valuation

Townsend, C., Neal, D. T., & Morgan, C. (2019) · Journal of Business Research · doi:10.1016/j.jbusres.2019.03.014 · Cited by 17

Social media as a recruitment method to reach a diverse sample of bereaved parents

Johnson, L. A., Dias, N., Clarkson, G., & Schreier, A. M. (2019) · Applied Nursing Research · doi:10.1016/j.apnr.2019.151201 · Cited by 17

Proposed conceptual framework of Dengue Active Surveillance System (DASS) in Malaysia

Othman, M. K. B., & Danuri, M. S. N. M. (2016) · doi:10.1109/icictm.2016.7890783 · Cited by 15

The Digital Age and the Future of Social Network Science and Engineering

Flack, J. C., & D’Souza, R. M. (2014) · Proceedings of the IEEE · doi:10.1109/jproc.2014.2368790 · Cited by 14

Prediction of Aggressive Comments in Social Media: an Exploratory Study

Bosque, L. P. D., & Garza, S. E. (2016) · IEEE Latin America Transactions · doi:10.1109/tla.2016.7587657 · Cited by 13

Socially-Driven Learning-Based Prefetching in Mobile Online Social Networks

Wu, C., Chen, X., Zhu, W., & Zhang, Y. (2017) · IEEE/ACM Transactions on Networking · doi:10.1109/tnet.2017.2681121 · Cited by 13

A hybrid epidemic model for deindividuation and antinormative behavior in online social networks

Liao, C., Squicciarini, A., Griffin, C. H., & Rajtmajer, S. M. (2016) · Social Network Analysis and Mining · doi:10.1007/s13278-016-0321-5 · Cited by 12

Unsupervised Many-to-Many Object Matching for Relational Data

Iwata, T., Lloyd, J. R., & Zoubin Ghahramani, A. (2015) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2015.2469284 · Cited by 12

Decision Learning : Data analytic learning with strategic decision making

Chen, Y., Jiang, C., Wang, C.-Y., Gao, Y., & Liu, K. J. R. (2015) · IEEE Signal Processing Magazine · doi:10.1109/msp.2015.2479895 · Cited by 11

Relational intelligence recognition in online social networks — A survey

Zhang, J., Tan, L., Tao, X., Pham, T., & Chen, B. (2020) · Computer Science Review · doi:10.1016/j.cosrev.2019.100221 · Cited by 9

Trust for online social media direct-to-consumer prescription medication advertisements

Fogel, J., & Adnan, M. (2019) · Health Policy and Technology · doi:10.1016/j.hlpt.2019.08.009 · Cited by 8

Analysis and Control of Beliefs in Social Networks

Wang, T., Krim, H., & Viniotis, Y. (2014) · IEEE Transactions on Signal Processing · doi:10.1109/tsp.2014.2352591 · Cited by 8

Twitter-based Influenza Surveillance

Comito, C., Forestiero, A., & Pizzuti, C. (2018) · International Database Engineering and Applications Symposium (IDEAS) · doi:10.1145/3216122.3216128 · Cited by 8

Aspect-Level Influence Discovery from Graphs

Hu, C., & Cao, H. (2016) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2016.2538223 · Cited by 7

Introduction to Bioinformatics

Martins, E. R. (2019) · Antonella Carvalho de Oliveira eBooks · doi:10.22533/at.ed.138191202 · Cited by 2

Model Evaluation

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A survey on sentiment analysis methods, applications, and challenges

Wankhade, M., Rao, A. C. S., & Kulkarni, C. (2022) · Artificial Intelligence Review · doi:10.1007/s10462-022-10144-1 · Cited by 1,892

Six Human-Centered Artificial Intelligence Grand Challenges

Ozmen Garibay, O., Winslow, B., Andolina, S., Antona, M., Bodenschatz, A., Coursaris, C., Falco, G., Fiore, S. M., Garibay, I., Grieman, K., et al. (2023) · International Journal of Human–Computer Interaction · doi:10.1080/10447318.2022.2153320 · Cited by 501

Deepfake detection using deep learning methods: A systematic and comprehensive review

Heidari, A., Jafari Navimipour, N., Dag, H., & Unal, M. (2024) · WIREs Data Mining and Knowledge Discovery · doi:10.1002/widm.1520 · Cited by 349

Data oversampling and imbalanced datasets: an investigation of performance for machine learning and feature engineering

Mujahid, M., Kına, E., Rustam, F., Villar, M. G., Alvarado, E. S., Díez, I. D. L. T., & Ashraf, I. (2024) · Journal Of Big Data · doi:10.1186/s40537-024-00943-4 · Cited by 304

A review of machine learning methods applied to structural dynamics and vibroacoustic

Cunha, B. Z., Droz, C., Zine, A., Foulard, S., & Ichchou, M. N. (2023) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2023.110535 · Cited by 176

A survey on machine learning algorithms for analyzing social media

Mahalle, A. M., & Bhaladhare, P. (2025) · AIP conference proceedings · doi:10.1063/5.0289543 · Cited by 1

Sosyal Medya Analitiğinde Makine Öğrenmesi Uygulamaları: Literatür İncelemesi

Dobrucalı, B., & İlter, B. (2020) · Journal of Yaşar University · doi:10.19168/jyasar.687093 · Cited by 1

Machine Learning for Social Network Analysis: A Systematic Literature ReviewPreprint

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Sentiment Analysis of Social Media Data Using Machine Learning

Lumade, S., Kadam, D., Paithane, M. K. P., & Salve, M. S. A. K. (2026) · Zenodo (CERN European Organization for Nuclear Research) · doi:10.5281/zenodo.20794487

A survey on machine learning techniques used in social media data analysis

Bajpai, A., & Gupta, Y. K. (2023) · AIP conference proceedings · doi:10.1063/5.0154568