{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,8]],"date-time":"2026-01-08T03:50:52Z","timestamp":1767844252974,"version":"3.49.0"},"reference-count":109,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2021,7,16]],"date-time":"2021-07-16T00:00:00Z","timestamp":1626393600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000006","name":"Office of Naval Research","doi-asserted-by":"publisher","award":["N000141812559"],"award-info":[{"award-number":["N000141812559"]}],"id":[{"id":"10.13039\/100000006","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Symmetry"],"abstract":"<jats:p>The goal of this study was to conduct a literature review of current approaches and techniques for identifying, understanding, and predicting human behaviors through mining a variety of sources of textual data with a focus on enabling classification of psychological behaviors regarding emotion, cognition, and social empathy. This review was performed using keyword searches in ISI Web of Science, Engineering Village Compendex, ProQuest Dissertations, and Google Scholar. Our findings show that, despite recent advancements in predicting human behaviors based on unstructured textual data, significant developments in data analytics systems for identification, determination of interrelationships, and prediction of human cognitive, emotional and social behaviors remain lacking.<\/jats:p>","DOI":"10.3390\/sym13071276","type":"journal-article","created":{"date-parts":[[2021,7,18]],"date-time":"2021-07-18T21:18:52Z","timestamp":1626643132000},"page":"1276","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Analysis of Human Behavior by Mining Textual Data: Current Research Topics and Analytical Techniques"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8128-5356","authenticated-orcid":false,"given":"Edgar","family":"Gutierrez","sequence":"first","affiliation":[{"name":"Department of Industrial Engineering and Management Systems, University of Central Florida, Orlando, FL 32816, USA"},{"name":"Center for Latin-American Logistics Innovation, Massachusetts Institute of Technology, Global SCALE, LOGyCA, Bogota 110111, Colombia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9134-3441","authenticated-orcid":false,"given":"Waldemar","family":"Karwowski","sequence":"additional","affiliation":[{"name":"Department of Industrial Engineering and Management Systems, University of Central Florida, Orlando, FL 32816, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5711-1498","authenticated-orcid":false,"given":"Krzysztof","family":"Fiok","sequence":"additional","affiliation":[{"name":"Department of Industrial Engineering and Management Systems, University of Central Florida, Orlando, FL 32816, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4021-1235","authenticated-orcid":false,"given":"Mohammad Reza","family":"Davahli","sequence":"additional","affiliation":[{"name":"Department of Industrial Engineering and Management Systems, University of Central Florida, Orlando, FL 32816, USA"}]},{"given":"Tameika","family":"Liciaga","sequence":"additional","affiliation":[{"name":"Department of Industrial Engineering and Management Systems, University of Central Florida, Orlando, FL 32816, USA"}]},{"given":"Tareq","family":"Ahram","sequence":"additional","affiliation":[{"name":"Department of Industrial Engineering and Management Systems, University of Central Florida, Orlando, FL 32816, USA"}]}],"member":"1968","published-online":{"date-parts":[[2021,7,16]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2845","DOI":"10.1016\/j.ins.2010.04.006","article-title":"Estimating Intrinsic Dimensionality Using the Multi-Criteria Decision Weighted Model and the Average Standard Estimator","volume":"180","author":"Ahram","year":"2010","journal-title":"Inf. Sci."},{"key":"ref_2","first-page":"1","article-title":"Sentiment Analysis and Opinion Mining","volume":"5","author":"Liu","year":"2012","journal-title":"Synth. Lect. Hum. Lang. Technol."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"559","DOI":"10.1080\/00223890802388459","article-title":"Clarifying the Linguistic Signature: Measuring Personality From Natural Speech","volume":"90","author":"Cohen","year":"2008","journal-title":"J. Pers. Assess."},{"key":"ref_4","unstructured":"Bornstein, M.H. (2021, March 21). Human Behavior|Definition, Theories, Characteristics, Examples, Types, & Facts. Available online: https:\/\/www.britannica.com\/topic\/human-behavior."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"24","DOI":"10.1177\/0261927X09351676","article-title":"The Psychological Meaning of Words: LIWC and Computerized Text Analysis Methods","volume":"29","author":"Tausczik","year":"2009","journal-title":"J. Lang. Soc. Psychol."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"291","DOI":"10.1037\/0022-3514.85.2.291","article-title":"Words of wisdom: Language use over the life span","volume":"85","author":"Pennebaker","year":"2003","journal-title":"J. Pers. Soc. Psychol."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"264","DOI":"10.7326\/0003-4819-151-4-200908180-00135","article-title":"Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement","volume":"151","author":"Moher","year":"2009","journal-title":"Ann. Intern. Med."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"d5928","DOI":"10.1136\/bmj.d5928","article-title":"The Cochrane Collaboration\u2019s tool for assessing risk of bias in randomised trials","volume":"343","author":"Higgins","year":"2011","journal-title":"BMJ"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"335","DOI":"10.1007\/s00779-014-0829-5","article-title":"Mobile phones as medical devices in mental disorder treatment: An overview","volume":"19","author":"Gravenhorst","year":"2015","journal-title":"Pers. Ubiquitous Comput."},{"key":"ref_10","first-page":"589","article-title":"Opinion Mining for Text Classification","volume":"2","author":"Mahendran","year":"2013","journal-title":"Int. J. Sci. Eng. Technol."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Binali, H.H., Wu, C., and Potdar, V. (2009, January 16\u201319). A new significant area: Emotion detection in E-learning using opinion mining techniques. Proceedings of the 2009 3rd IEEE International Conference on Digital Ecosystems and Technologies, Lake Ohrid, Macedonia.","DOI":"10.1109\/DEST.2009.5276726"},{"key":"ref_12","first-page":"1","article-title":"Modeling Public Mood and Emotion: Twitter Sentiment and Socio-Economic Phenomena","volume":"5","author":"Bollen","year":"2011","journal-title":"Proc. Int. AAAI Conf. Web Soc. Media"},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Bespalov, D., Bai, B., Qi, Y., and Shokoufandeh, A. (2011, January 24\u201328). Sentiment Classification Based on Supervised Latent N-Gram Analysis. Proceedings of the 20th ACM International Conference on Information and Knowledge Management, Glasgow Scotland, UK.","DOI":"10.1145\/2063576.2063635"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Frost, M., Doryab, A., Faurholt-Jepsen, M., Kessing, L.V., and Bardram, J.E. (2013, January 8\u201312). Supporting Disease Insight through Data Analysis: Refinements of the Monarca Self-Assessment System. Proceedings of the 2013 ACM International Joint Conference on Pervasive and Ubiquitous Computing, Zurich, Switzerland.","DOI":"10.1145\/2493432.2493507"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"140","DOI":"10.1109\/JBHI.2014.2343154","article-title":"Smartphone-Based Recognition of States and State Changes in Bipolar Disorder Patients","volume":"19","author":"Grunerbl","year":"2015","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Hu, M., and Liu, B. (2004, January 22\u201325). Mining and summarizing customer reviews. Proceedings of the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Seattle, DC, USA.","DOI":"10.1145\/1014052.1014073"},{"key":"ref_17","unstructured":"Miedema, F. (2018). Sentiment Analysis with Long Short-Term Memory Networks, Vrije Universiteit Amsterdam."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Pang, B., Lee, L., and Vaithyanathan, S. (2002). Thumbs up? Sentiment Classification Using Machine Learning Techniques. arXiv.","DOI":"10.3115\/1118693.1118704"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Arora, R., and Srinivasa, S. A Faceted Characterization of the Opinion Mining Landscape. Proceedings of the 2014 Sixth International Conference on Communication Systems and Networks.","DOI":"10.1109\/COMSNETS.2014.6734936"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"127","DOI":"10.25046\/aj020115","article-title":"A Survey of Text Mining in Social Media: Facebook and Twitter Perspectives","volume":"2","author":"Salloum","year":"2017","journal-title":"Adv. Sci. Technol. Eng. Syst. J."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Turney, P.D. (2002). Thumbs Up or Thumbs Down? Semantic Orientation Applied to Unsupervised Classification of Reviews. arXiv.","DOI":"10.3115\/1073083.1073153"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"453","DOI":"10.1016\/j.proeng.2013.02.059","article-title":"Opinion Mining of Movie Review using Hybrid Method of Support Vector Machine and Particle Swarm Optimization","volume":"53","author":"Basari","year":"2013","journal-title":"Procedia Eng."},{"key":"ref_23","first-page":"126","article-title":"Product Aspect Ranking Using Sentiment Analysis: A Survey","volume":"3","author":"Mate","year":"2015","journal-title":"Int. Res. J. Eng. Technol."},{"key":"ref_24","first-page":"321","article-title":"Opinion Mining and Sentimental Analysis Approaches: A Survey","volume":"11","author":"Othman","year":"2014","journal-title":"Life Sci. J."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1561\/1500000011","article-title":"Opinion Mining and Sentiment Analysis","volume":"2","author":"Pang","year":"2008","journal-title":"Found. Trends\u00ae Inf. Retr."},{"key":"ref_26","first-page":"282","article-title":"Sentiment Analysis and Opinion Mining: A Survey","volume":"2","author":"Vinodhini","year":"2012","journal-title":"Int. J."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"e43","DOI":"10.2196\/mental.8141","article-title":"#MyDepressionLooksLike: Examining Public Discourse About Depression on Twitter","volume":"4","author":"Lachmar","year":"2017","journal-title":"JMIR Ment. Health."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Wu, H., Liu, K., and Trappey, C. Understanding Customers Using Facebook Pages: Data Mining Users Feedback Using Text Analysis. Proceedings of the 2014 IEEE 18th International Conference on Computer Supported Cooperative Work in Design (CSCWD).","DOI":"10.1109\/CSCWD.2014.6846867"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Davis, P.K., Manheim, D., Perry, W.L., and Hollywood, J. Using causal models in heterogeneous information fusion to detect terrorists. Proceedings of the 2015 Winter Simulation Conference (WSC).","DOI":"10.1109\/WSC.2015.7408367"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Hung, B.W.K., Jayasumana, A.P., and Bandara, V.W. (2017, January 25\u201326). INSiGHT: A System for Detecting Radicalization Trajectories in Large Heterogeneous Graphs. Proceedings of the 2017 IEEE International Symposium on Technologies for Homeland Security (HST), Waltham, MA, USA.","DOI":"10.1109\/THS.2017.7943441"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/2190-8532-2-11","article-title":"Harvesting and analysis of weak signals for detecting lone wolf terrorists","volume":"2","author":"Brynielsson","year":"2013","journal-title":"Secur. Inform."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"246","DOI":"10.1080\/09546553.2014.849948","article-title":"Detecting Linguistic Markers for Radical Violence in Social Media","volume":"26","author":"Cohen","year":"2013","journal-title":"Terror. Polit. Violence"},{"key":"ref_33","unstructured":"Gill, A.J. (2003). Personality and Language: The Projection and Perception of Personality in Computer-Mediated Communication. [Ph.D. Thesis, University of Edinburgh]."},{"key":"ref_34","unstructured":"Banati, H., Bhattacharyya, S., Mani, A., and K\u00f6ppen, M. (2017). Hierarchical Sentiment Analysis Model for Automatic Review Classification for E-commerce Users. Hybrid Intelligence for Social Networks, Springer International Publishing."},{"key":"ref_35","unstructured":"Cipresso, P., Matic, A., Gr\u00fcnerbl, A., Lopez, G., and Tr\u00f6ster, G. Assessing Bipolar Episodes Using Speech Cues Derived from Phone Calls. Proceedings of the Pervasive Computing Paradigms for Mental Health."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Davis, P.K., Perry, W.L., Brown, R.A., Yeung, D., Roshan, P., and Voorhies, P. (2013). Using Behavioral Indicators to Help Detect Potential Violent Acts, RAND Corporation.","DOI":"10.7249\/RB9724"},{"key":"ref_37","unstructured":"Nasukawa, T., and Yi, J. Sentiment Analysis: Capturing Favorability Using Natural Language Processing. Proceedings of the Proceedings of the 2nd International Conference on Knowledge Capture."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"211","DOI":"10.1016\/j.knosys.2017.11.021","article-title":"Identifying topical influencers on twitter based on user behavior and network topology","volume":"141","author":"Alp","year":"2018","journal-title":"Knowl. Based Syst."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"63","DOI":"10.1016\/j.cobeha.2017.07.017","article-title":"Language-based personality: A new approach to personality in a digital world","volume":"18","author":"Boyd","year":"2017","journal-title":"Curr. Opin. Behav. Sci."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"259","DOI":"10.1348\/014466509X467828","article-title":"The efficacy of SMS text messages to compensate for the effects of cognitive impairments in schizophrenia","volume":"49","author":"Pijnenborg","year":"2010","journal-title":"Br. J. Clin. Psychol."},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Gamon, M. (2004, January 23\u201327). Sentiment Classification on Customer Feedback Data: Noisy Data, Large Feature Vectors, and the Role of Linguistic Analysis. Proceedings of the COLING 2004: Proceedings of the 20th International Conference on Computational Linguistics, Geneva, Switzerland.","DOI":"10.3115\/1220355.1220476"},{"key":"ref_42","unstructured":"Pennebaker, J.W., Boyd, R.L., Jordan, K., and Blackburn, K. (2015). The Development and Psychometric Properties of LIWC2015, University of Texas at Austin."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"26","DOI":"10.1016\/j.procs.2013.05.005","article-title":"The Role of Text Pre-processing in Sentiment Analysis","volume":"17","author":"Haddi","year":"2013","journal-title":"Procedia Comput. Sci."},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Li, D., and Qian, J. (2016, January 13\u201315). Text Sentiment Analysis Based on Long Short-Term Memory. Proceedings of the 2016 First IEEE International Conference on Computer Communication and the Internet (ICCCI), Wuhan, China.","DOI":"10.1109\/CCI.2016.7778967"},{"key":"ref_45","first-page":"232","article-title":"Analysing the presence of school-shooting related communities at social media sites","volume":"1","author":"Semenov","year":"2010","journal-title":"Int. J. Multimed. Intell. Secur."},{"key":"ref_46","unstructured":"Bartlett, J., and Reynolds, L. (2015). The State of the Art 2015: A Literature Review of Social Media Intelligence Capabilities for Counter-Terrorism, Demos London; Demos."},{"key":"ref_47","first-page":"99","article-title":"Opinion Mining Platform for Intelligence in Business","volume":"3","author":"Bucur","year":"2014","journal-title":"Econ. Insights Trends Chall."},{"key":"ref_48","unstructured":"Dave, K., Lawrence, S., and Pennock, D.M. Mining the Peanut Gallery: Opinion Extraction and Semantic Classification of Product Reviews. Proceedings of the 12th International Conference on World Wide Web."},{"key":"ref_49","unstructured":"Meiselwitz, G. Analysis of Online Social Networks Posts to Investigate Suspects Using SEMCON. Proceedings of the Social Computing and Social Media."},{"key":"ref_50","unstructured":"Nahm, U.Y., and Mooney, R.J. (2000, January 1\u20133). A Mutually Beneficial Integration of Data Mining and Information Extraction. Proceedings of the AAAI\/IAAI, Austin, TX, USA."},{"key":"ref_51","first-page":"1211","article-title":"Product Aspect Ranking and Its Applications","volume":"26","author":"Zha","year":"2013","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"ref_52","first-page":"261","article-title":"Opinion Zoom: A Modular Tool to Explore Tourism Opinions on the Web","volume":"Volume 3","year":"2013","journal-title":"Proceedings of the 2013 IEEE\/WIC\/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT)"},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"757","DOI":"10.1007\/s11135-018-0787-5","article-title":"Language and Interaction: Applying Sociolinguistics to Social Network Analysis","volume":"53","author":"Diehl","year":"2019","journal-title":"Qual. Quant."},{"key":"ref_54","doi-asserted-by":"crossref","unstructured":"Semenov, A., Veijalainen, J., and Boukhanovsky, A. (2011, January 7\u20139). A Generic Architecture for a Social Network Monitoring and Analysis System. Proceedings of the 2011 14th International Conference on Network-Based Information Systems, Tirana, Albania.","DOI":"10.1109\/NBiS.2011.52"},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"100","DOI":"10.1016\/j.procs.2017.11.150","article-title":"Mind Mapping: Using Everyday Language to Explore Social & Psychological Processes","volume":"118","author":"Pennebaker","year":"2017","journal-title":"Procedia Comput. Sci."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"48","DOI":"10.1145\/1105664.1105679","article-title":"Information Extraction: Distilling Structured Data from Unstructured Text","volume":"3","author":"McCallum","year":"2005","journal-title":"Queue"},{"key":"ref_57","doi-asserted-by":"crossref","unstructured":"Ibrahim, M., and Ahmad, R. (2010, January 7\u201310). Class Diagram Extraction from Textual Requirements Using Natural Language Processing (NLP) Techniques. Proceedings of the 2010 Second International Conference on Computer Research and Development, Kuala Lumpur, Malaysia.","DOI":"10.1109\/ICCRD.2010.71"},{"key":"ref_58","doi-asserted-by":"crossref","unstructured":"Eichinger, T., Beierle, F., Khan, S.U., and Middelanis, R. (2019, January 20\u201324). Affinity: A System for Latent User Similarity Comparison on Texting Data. Proceedings of the ICC 2019\u20142019 IEEE International Conference on Communications (ICC), Shanghai, China.","DOI":"10.1109\/ICC.2019.8761051"},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"1014","DOI":"10.1016\/j.chb.2012.01.003","article-title":"Automated Computer-Based Feedback in Expressive Writing. Comput","volume":"28","author":"Bond","year":"2012","journal-title":"Hum. Behav."},{"key":"ref_60","unstructured":"National Research Council (2011). Intelligence Analysis: Behavioral and Social Scientific Foundations, National Academies Press."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"96","DOI":"10.1016\/j.jrp.2007.04.006","article-title":"Revealing Dimensions of Thinking in Open-Ended Self-Descriptions: An Automated Meaning Extraction Method for Natural Language","volume":"42","author":"Chung","year":"2008","journal-title":"J. Res. Personal."},{"key":"ref_62","unstructured":"Rizzi, A., Vichi, M., and Bock, H.-H. Text Mining-Knowledge Extraction from Unstructured Textual Data. Proceedings of the Advances in Data Science and Classification."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"95","DOI":"10.1016\/j.inffus.2015.06.002","article-title":"Opinion Mining and Information Fusion: A Survey","volume":"27","author":"Balazs","year":"2016","journal-title":"Inf. Fusion"},{"key":"ref_64","unstructured":"Chakraborty, G., Pagolu, M., and Garla, S. (2014). Text Mining and Analysis: Practical Methods, Examples, and Case Studies Using SAS, SAS Institute."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/360402.360406","article-title":"Web Mining Research: A Survey","volume":"2","author":"Kosala","year":"2000","journal-title":"ACM SIGKDD Explor. Newsl."},{"key":"ref_66","unstructured":"Manning, C., and Schutze, H. (1999). Foundations of Statistical Natural Language Processing, MIT Press."},{"key":"ref_67","unstructured":"Nigam, K., Lafferty, J., and McCallum, A. (1999, January 1). Using Maximum Entropy for Text Classification. Proceedings of the IJCAI-99 Workshop on Machine Learning for Information Filtering, Stockholom, Sweden."},{"key":"ref_68","doi-asserted-by":"crossref","unstructured":"Shahbaz, M., Guergachi, A., and Rehman, R.T. (2014, January 4\u20137th). ur Sentiment Miner: A Prototype for Sentiment Analysis of Unstructured Data and Text. Proceedings of the 2014 IEEE 27th Canadian Conference on Electrical and Computer Engineering (CCECE), Toronto, ON, Canada.","DOI":"10.1109\/CCECE.2014.6901087"},{"key":"ref_69","unstructured":"Weiss, S.M., Indurkhya, N., Zhang, T., and Damerau, F. (2010). Text Mining: Predictive Methods for Analyzing Unstructured Information, Springer Science & Business Media."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"841","DOI":"10.1089\/cpb.2007.9943","article-title":"Development of a Scale to Measure Problem Use of Short Message Service: The SMS Problem Use Diagnostic Questionnaire","volume":"10","author":"Rutland","year":"2007","journal-title":"Cyberpsychol. Behav."},{"key":"ref_71","doi-asserted-by":"crossref","unstructured":"Aggarwal, C.C., and Zhai, C. (2012). An introduction to text mining. Mining Text Data, Springer.","DOI":"10.1007\/978-1-4614-3223-4"},{"key":"ref_72","doi-asserted-by":"crossref","unstructured":"Berry, M.W., and Kogan, J. (2010). Text Mining: Applications and Theory, John Wiley & Sons.","DOI":"10.1002\/9780470689646"},{"key":"ref_73","doi-asserted-by":"crossref","unstructured":"Akilan, A. (2015, January 26\u201327). Text Mining: Challenges and Future Directions. Proceedings of the 2015 2nd International Conference on Electronics and Communication Systems (ICECS), Coimbatore, India.","DOI":"10.1109\/ECS.2015.7124872"},{"key":"ref_74","unstructured":"Weerdt, J.D., vanden Broucke, S.K., Vanthienen, J., and Baesens, B. (2012, January 10\u201315). Leveraging Process Discovery with Trace Clustering and Text Mining for Intelligent Analysis of Incident Management Processes. Proceedings of the 2012 IEEE Congress on Evolutionary Computation, Brisbane, Australia."},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"621","DOI":"10.1016\/j.eswa.2012.07.059","article-title":"Document-Level Sentiment Classification: An Empirical Comparison between SVM and ANN","volume":"40","author":"Moraes","year":"2013","journal-title":"Expert Syst. Appl."},{"key":"ref_76","unstructured":"Fraley, R.C. (2004). How to Conduct Behavioral Research over the Internet: A Beginner\u2019s Guide to HTML and CGI\/Perl, Guilford Press."},{"key":"ref_77","doi-asserted-by":"crossref","first-page":"101934","DOI":"10.1016\/j.ijinfomgt.2019.04.007","article-title":"Emotional Text Mining: Customer Profiling in Brand Management","volume":"51","author":"Greco","year":"2020","journal-title":"Int. J. Inf. Manag."},{"key":"ref_78","doi-asserted-by":"crossref","first-page":"e12189","DOI":"10.1002\/eng2.12189","article-title":"Text-Based Emotion Detection: Advances, Challenges, and Opportunities","volume":"2","author":"Acheampong","year":"2020","journal-title":"Eng. Rep."},{"key":"ref_79","doi-asserted-by":"crossref","first-page":"113265","DOI":"10.1016\/j.eswa.2020.113265","article-title":"Opinion Mining and Emotion Recognition Applied to Learning Environments","volume":"150","author":"Estrada","year":"2020","journal-title":"Expert Syst. Appl."},{"key":"ref_80","doi-asserted-by":"crossref","unstructured":"Wang, X., Kou, L., Sugumaran, V., Luo, X., and Zhang, H. (2020). Emotion Correlation Mining through Deep Learning Models on Natural Language Text. IEEE Trans. Cybern.","DOI":"10.1109\/TCYB.2020.2987064"},{"key":"ref_81","doi-asserted-by":"crossref","first-page":"100979","DOI":"10.1016\/j.stueduc.2021.100979","article-title":"Using Opinion Mining as an Educational Analytic: An Integrated Strategy for the Analysis of Students\u2019 Feedback","volume":"68","author":"Misuraca","year":"2021","journal-title":"Stud. Educ. Eval."},{"key":"ref_82","first-page":"43","article-title":"Text Analytics of Customers on Twitter: Brand Sentiments in Customer Support","volume":"11","year":"2019","journal-title":"J. Inf. Technol. Manag."},{"key":"ref_83","doi-asserted-by":"crossref","unstructured":"Swain, D., Khandelwal, A., Joshi, C., Gawas, A., Roy, P., and Zad, V. (2021). A Suicide Prediction System Based on Twitter Tweets Using Sentiment Analysis and Machine Learning. Machine Learning and Information Processing: Proceedings of ICMLIP 2020, Springer.","DOI":"10.1007\/978-981-33-4859-2_5"},{"key":"ref_84","unstructured":"Saire, J.E.C., and Cruz, J.F.O. (2020). Study of Coronavirus Impact on Parisian Population from April to June Using Twitter and Text Mining Approach. 2020 International Computer Symposium, IEEE."},{"key":"ref_85","unstructured":"Chire-Saire, J.E. (2020). Characterizing Twitter Interaction during COVID-19 Pandemic Using Complex Networks and Text Mining. arXiv Prepr."},{"key":"ref_86","doi-asserted-by":"crossref","first-page":"103222","DOI":"10.1016\/j.compind.2020.103222","article-title":"Estimating Industry 4.0 Impact on Job Profiles and Skills Using Text Mining","volume":"118","author":"Fareri","year":"2020","journal-title":"Comput. Ind."},{"key":"ref_87","first-page":"1","article-title":"When Emotions Rule Knowledge: A Text-Mining Study of Emotions in Knowledge Management Research","volume":"17","author":"Fteimi","year":"2021","journal-title":"Int. J. Knowl. Manag. IJKM"},{"key":"ref_88","doi-asserted-by":"crossref","unstructured":"Bayram, U., and Benhiba, L. (2021, January 11). Determining a Person\u2019s Suicide Risk by Voting on the Short-Term History of Tweets for the CLPsych 2021 Shared Task. Proceedings of the Proceedings of the Seventh Workshop on Computational Linguistics and Clinical Psychology: Improving Access, Mexico City, Mexico.","DOI":"10.18653\/v1\/2021.clpsych-1.8"},{"key":"ref_89","doi-asserted-by":"crossref","unstructured":"Davahli, M.R., Karwowski, W., Gutierrez, E., Fiok, K., Wr\u00f3bel, G., Taiar, R., and Ahram, T. (2020). Identification and Prediction of Human Behavior through Mining of Unstructured Textual Data. Symmetry, 12.","DOI":"10.3390\/sym12111902"},{"key":"ref_90","unstructured":"Siby, S. (2020, January 21\u201323). An Exploration about the Last Mile Logistic Efficiency in Indian E-Commerce Sector\u2014A Text Mining Approach. Proceedings of the International Conference on Innovative Computing & Communications (ICICC), New Delhi, India. Available online: https:\/\/ssrn.com\/abstract=3563089."},{"key":"ref_91","doi-asserted-by":"crossref","first-page":"735","DOI":"10.1007\/s10955-014-1024-9","article-title":"Saving Human Lives: What Complexity Science and Information Systems Can Contribute","volume":"158","author":"Helbing","year":"2015","journal-title":"J. Stat. Phys."},{"key":"ref_92","doi-asserted-by":"crossref","unstructured":"Huang, H.H., Yang, Y.C., Hsiao, C.T., Liang, H.C., and Liu, C.S. (2010, January 2\u20135). The National Health Insurance: Decoding the Health Bill. Proceedings of the 2010 IEEE International Conference on Management of Innovation Technology, Singapore.","DOI":"10.1109\/ICMIT.2010.5492783"},{"key":"ref_93","doi-asserted-by":"crossref","unstructured":"Bakshi, K. (2012, January 3\u201310). Considerations for Big Data: Architecture and Approach. Proceedings of the 2012 IEEE Aerospace Conference, Big Sky, MT, USA.","DOI":"10.1109\/AERO.2012.6187357"},{"key":"ref_94","first-page":"414","article-title":"Text Mining: Techniques, Applications and Issues","volume":"7","author":"Talib","year":"2016","journal-title":"Int. J. Adv. Comput. Sci. Appl."},{"key":"ref_95","unstructured":"Guti\u00e9rrez, E., Bhide, S., and Mendizabal, L.C.R. (2018). Artificial Intelligence: Advances in Research and Applications, Nova Science Publishers."},{"key":"ref_96","doi-asserted-by":"crossref","unstructured":"Sarawagi, S. (2008). Information Extraction, Now Publishers Inc.","DOI":"10.1561\/9781601981899"},{"key":"ref_97","doi-asserted-by":"crossref","first-page":"1336","DOI":"10.1109\/TKDE.2012.51","article-title":"Nonnegative Matrix Factorization: A Comprehensive Review","volume":"25","author":"Wang","year":"2012","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"ref_98","first-page":"993","article-title":"Latent Dirichlet Allocation","volume":"3","author":"Blei","year":"2003","journal-title":"J. Mach. Learn. Res."},{"key":"ref_99","doi-asserted-by":"crossref","unstructured":"Kowsari, K., Jafari Meimandi, K., Heidarysafa, M., Mendu, S., Barnes, L., and Brown, D. (2019). Text Classification Algorithms: A Survey. Information, 10.","DOI":"10.3390\/info10040150"},{"key":"ref_100","first-page":"82","article-title":"Clustering Techniques: A Brief Survey of Different Clustering Algorithms","volume":"1","author":"Sisodia","year":"2012","journal-title":"Int. J. Latest Trends Eng. Technol. IJLTET"},{"key":"ref_101","first-page":"253","article-title":"Study of Abstractive Text Summarization Techniques","volume":"6","author":"Yeasmin","year":"2017","journal-title":"Am. J. Eng. Res."},{"key":"ref_102","first-page":"207","article-title":"Natural Language Processing: A Review","volume":"6","author":"Joseph","year":"2016","journal-title":"Nat. Lang. Process. Rev."},{"key":"ref_103","first-page":"1543","article-title":"Web Mining Overview, Techniques, Tools and Applications: A Survey","volume":"3","author":"Kumar","year":"2016","journal-title":"Int. Res. J. Eng. Technol. IRJET"},{"key":"ref_104","doi-asserted-by":"crossref","first-page":"755","DOI":"10.1080\/02643290701754158","article-title":"A Time to Think: Circadian Rhythms in Human Cognition","volume":"24","author":"Schmidt","year":"2007","journal-title":"Cogn. Neuropsychol."},{"key":"ref_105","doi-asserted-by":"crossref","unstructured":"Thakur, N., and Han, C.Y. (2018, January 15\u201318). An Approach to Analyze the Social Acceptance of Virtual Assistants by Elderly People. Proceedings of the 8th International Conference on the Internet of Things, Santa Barbara, CA, USA.","DOI":"10.1145\/3277593.3277616"},{"key":"ref_106","unstructured":"Fischhoff, B., and Chauvin, C. (2021, March 21). Intelligence Analysis. Behav. Soc., Available online: https:\/\/www.nap.edu\/read\/13062\/chapter\/1#ii."},{"key":"ref_107","unstructured":"Granmo, O.-C. (2018). The Tsetlin Machine\u2013A Game Theoretic Bandit Driven Approach to Optimal Pattern Recognition with Propositional Logic. arXiv Prepr."},{"key":"ref_108","doi-asserted-by":"crossref","first-page":"601","DOI":"10.1109\/TNNLS.2018.2846646","article-title":"Dendritic Neuron Model with Effective Learning Algorithms for Classification, Approximation, and Prediction","volume":"30","author":"Gao","year":"2018","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"ref_109","unstructured":"Chakraborty, G., and Krishna, M. (2014, January 23\u201326). Analysis of Unstructured Data: Applications of Text Analytics and Sentiment Mining. Proceedings of the SAS Global Forum, Washington, DC, USA."}],"container-title":["Symmetry"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2073-8994\/13\/7\/1276\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T06:31:26Z","timestamp":1760164286000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2073-8994\/13\/7\/1276"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,7,16]]},"references-count":109,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2021,7]]}},"alternative-id":["sym13071276"],"URL":"https:\/\/doi.org\/10.3390\/sym13071276","relation":{},"ISSN":["2073-8994"],"issn-type":[{"value":"2073-8994","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,7,16]]}}}