Probabilistic topic models

Machine learning: Trends, perspectives, and prospects

Jordan, M. I., & Mitchell, T. M. (2015) · Science · doi:10.1126/science.aaa8415 · Cited by 9,955 · see citing works

Business intelligence and analytics: from big data to big impact

Chen, H., Chiang, R. H. L., & Storey, V. C. (2012) · MIS Quarterly · doi:10.2307/41703503 · Cited by 6,250 · see citing works

Text as Data: The Promise and Pitfalls of Automatic Content Analysis Methods for Political Texts

Grimmer, J., & Stewart, B. M. (2013) · Political Analysis · doi:10.1093/pan/mps028 · Cited by 3,297 · see citing works

Deep patient: An unsupervised representation to predict the future of patients from the electronic health records

Miotto, R., Li, L., Kidd, B. A., & Dudley, J. T. (2016) · Scientific Reports · doi:10.1038/srep26094 · Cited by 1,710 · see citing works

Toward Scalable Systems for Big Data Analytics: A Technology Tutorial

Hu, H., Wen, Y., Chua, T.-S., & Li, X. (2014) · IEEE Access · doi:10.1109/access.2014.2332453 · Cited by 1,099 · see citing works

The evolution of 10-K textual disclosure: Evidence from Latent Dirichlet Allocation

Dyer, T., Lang, M., & Stice-Lawrence, L. (2017) · Journal of Accounting and Economics · doi:10.1016/j.jacceco.2017.07.002 · Cited by 841 · see citing works

Data integration enables global biodiversity synthesis

Heberling, J. M., Miller, J. T., Noesgaard, D., Weingart, S. B., & Schigel, D. (2021) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2018093118 · Cited by 380 · see citing works

Predicting academic performance: a systematic literature review

Hellas, A., Ihantola, P., Petersen, A., Ajanovski, V. V., Gutica, M., Hynninen, T., Knutas, A., Leinonen, J., Messom, C., & Liao, S. N. (2018) · Proceedings Companion of the 23rd Annual ACM Conference on Innovation and Technology in Computer Science Education · doi:10.1145/3293881.3295783 · Cited by 355 · see citing works

Topic Modeling as a Strategy of Inquiry in Organizational Research: A Tutorial With an Application Example on Organizational Culture

Schmiedel, T., Müller, O., & vom Brocke, J. (2019) · Organizational Research Methods · doi:10.1177/1094428118773858 · Cited by 319 · see citing works

revtools: An R package to support article screening for evidence synthesis

Westgate, M. J. (2019) · Research Synthesis Methods · doi:10.1002/jrsm.1374 · Cited by 261 · see citing works

Sentiment Aware Fake News Detection on Online Social Networks

Ajao, O., Bhowmik, D., & Zargari, S. (2019) · ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) · doi:10.1109/icassp.2019.8683170 · Cited by 228 · see citing works

Uncovering and Mitigating Algorithmic Bias through Learned Latent Structure

Amini, A., Soleimany, A. P., Schwarting, W., Bhatia, S. N., & Rus, D. (2019) · Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society · doi:10.1145/3306618.3314243 · Cited by 206 · see citing works

Text mining for information systems researchers: An annotated topic modeling tutorial

University of Liechtenstein, Debortoli, S., Müller, O., IT University of Copenhagen, Junglas, I., Florida State University, vom Brocke, J., & University of Liechtenstein (2016) · Communications of the Association for Information Systems · doi:10.17705/1cais.03907 · Cited by 199 · see citing works

SWIFT-Review: a text-mining workbench for systematic review

Howard, B. E., Phillips, J., Miller, K., Tandon, A., Mav, D., Shah, M. R., Holmgren, S., Pelch, K. E., Walker, V., Rooney, A. A., et al. (2016) · Systematic Reviews · doi:10.1186/s13643-016-0263-z · Cited by 196 · see citing works

Linear Algebraic Structure of Word Senses, with Applications to Polysemy

Arora, S., Li, Y., Liang, Y., Ma, T., & Risteski, A. (2018) · Transactions of the Association for Computational Linguistics · doi:10.1162/tacl_a_00034 · Cited by 186 · see citing works

Opportunities and challenges of text mining in materials research

Kononova, O., He, T., Huo, H., Trewartha, A., Olivetti, E. A., & Ceder, G. (2021) · iScience · doi:10.1016/j.isci.2021.102155 · Cited by 182 · see citing works

Predictive Modeling of the Hospital Readmission Risk from Patients’ Claims Data Using Machine Learning: A Case Study on COPD

Min, X., Yu, B., & Wang, F. (2019) · Scientific Reports · doi:10.1038/s41598-019-39071-y · Cited by 170 · see citing works

The utility of topic modelling for discourse studies: a critical evaluation

Brookes, G., & McEnery, T. (2019) · Discourse Studies · doi:10.1177/1461445618814032 · Cited by 175 · see citing works

Semi-supervised machine-learning classification of materials synthesis procedures

Huo, H., Rong, Z., Kononova, O., Sun, W., Botari, T., He, T., Tshitoyan, V., & Ceder, G. (2019) · npj Computational Materials · doi:10.1038/s41524-019-0204-1 · Cited by 151 · see citing works

Retweets of officials’ alarming vs reassuring messages during the COVID-19 pandemic: Implications for crisis management

Rao, H. R., Vemprala, N., Akello, P., & Valecha, R. (2020) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2020.102187 · Cited by 150 · see citing works

Collective sense-making in times of crisis: Connecting terror management theory with Twitter user reactions to the Berlin terrorist attack

Fischer-Preßler, D., Schwemmer, C., & Fischbach, K. (2019) · Computers in Human Behavior · doi:10.1016/j.chb.2019.05.012 · Cited by 133 · see citing works

Topic based classification and pattern identification in patents

Venugopalan, S., & Rai, V. (2015) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2014.10.006 · Cited by 116 · see citing works

Plant Phenotyping using Probabilistic Topic Models: Uncovering the Hyperspectral Language of Plants

Wahabzada, M., Mahlein, A.-K., Bauckhage, C., Steiner, U., Oerke, E.-C., & Kersting, K. (2016) · Scientific Reports · doi:10.1038/srep22482 · Cited by 118 · see citing works

Transformative privacy calculus: Conceptualizing the personalization‐privacy paradox on social media

Cloarec, J., Meyer‐Waarden, L., & Munzel, A. (2024) · Psychology & Marketing · doi:10.1002/mar.21998 · Cited by 104 · see citing works

Authorship Attribution with Topic Models

Seroussi, Y., Zukerman, I., & Bohnert, F. (2014) · Computational Linguistics · doi:10.1162/coli_a_00173 · Cited by 89 · see citing works

A Survey of Machine Learning for Big Code and Naturalness

Allamanis, M., Barr, E. T., Devanbu, P., & Sutton, C. (2019) · ACM Computing Surveys · doi:10.1145/3212695 · Cited by 150 · see citing works

MIRA: joint regulatory modeling of multimodal expression and chromatin accessibility in single cells

Lynch, A. W., Theodoris, C. V., Long, H. W., Brown, M., Liu, X. S., & Meyer, C. A. (2022) · Nature Methods · doi:10.1038/s41592-022-01595-z · Cited by 80 · see citing works

Text mining to support abstract screening for knowledge syntheses: a semi-automated workflow

Pham, B., Jovanovic, J., Bagheri, E., Antony, J., Ashoor, H., Nguyen, T. T., Rios, P., Robson, R., Thomas, S. M., Watt, J., et al. (2021) · Systematic Reviews · doi:10.1186/s13643-021-01700-x · Cited by 63 · see citing works

How African countries respond to fake news and hate speech

Garbe, L., Selvik, L.-M., & Lemaire, P. (2023) · Information, Communication & Society · doi:10.1080/1369118x.2021.1994623 · Cited by 57 · see citing works

Ethical use of artificial intelligence based tools in higher education: Are future business leaders ready?

Mumtaz, S., Carmichael, J., Weiss, M., & Nimon-Peters, A. (2025) · Education and Information Technologies · doi:10.1007/s10639-024-13099-8 · Cited by 55 · see citing works

Public Opinion on Dockless Bike Sharing: A Machine Learning Approach

Rahim Taleqani, A., Hough, J., & Nygard, K. E. (2019) · Transportation Research Record: Journal of the Transportation Research Board · doi:10.1177/0361198119838982 · Cited by 47 · see citing works

Mixed-Initiative Real-Time Topic Modeling & Visualization for Crisis Counseling

Dinakar, K., Chen, J., Lieberman, H., Picard, R., & Filbin, R. (2015) · Proceedings of the 20th International Conference on Intelligent User Interfaces · doi:10.1145/2678025.2701395 · Cited by 42 · see citing works

How Verb Tense Shapes Persuasion

Packard, G., Berger, J., & Boghrati, R. (2023) · Journal of Consumer Research · doi:10.1093/jcr/ucad006 · Cited by 36 · see citing works

#MyPrivacy: How Users Think About Social Media Privacy

Quinn, K., & Epstein, D. (2018) · Proceedings of the 9th International Conference on Social Media and Society · doi:10.1145/3217804.3217945 · Cited by 17 · see citing works

Analysing User Reviews in Tourism with Topic Models

Rossetti, M., Stella, F., Cao, L., & Zanker, M. (2015) · Information and Communication Technologies in Tourism 2015 · doi:10.1007/978-3-319-14343-9_4 · Cited by 13 · see citing works

26 years left behind: a historical and predictive analysis of electronic business research

Ozansoy Çadırcı, T., & Sağkaya Güngör, A. (2021) · Electronic Commerce Research · doi:10.1007/s10660-021-09459-y · Cited by 11 · see citing works