Print Email Facebook Twitter Tweetology of Learning Analytics Title Tweetology of Learning Analytics: What does Twitter tell us about the trends and development of the field? Author Khalil, Mohammad (University of Bergen) Wong, L.Y.J. (TU Delft Statistics) Er, Erkan (Middle East Technical University) Heitmann, Martin (University of Bergen) Belokrys, Gleb (University of Bergen) Date 2022 Abstract Twitter is a very popular microblogging platform that has been actively used by scientific communities to exchange scientific information and to promote scholarly discussions. The present study aimed to leverage the tweet data to provide valuable insights into the development of the learning analytics field since its initial days. Descriptive analysis, geocoding analysis, and topic modeling were performed on over 1.6 million tweets related to learning analytics posted between 2010-2021. The descriptive analysis reveals an increasing popularity of the field on the Twittersphere in terms of number of users, twitter posts, and hashtags emergence. The topic modeling analysis uncovers new insights of the major topics in the field of learning analytics. Emergent themes in the field were identified, and the increasing (e.g., Artificial Intelligence) and decreasing (e.g., Education) trends were shared. Finally, the geocoding analysis indicates an increasing participation in the field from more diverse countries all around the world. Further findings are discussed in the paper. Subject geospatial analysislearning analyticstopic modelingTwitterTwitter analysis To reference this document use: http://resolver.tudelft.nl/uuid:f6bef77a-2f9b-475e-a44e-f30d6a4e14eb DOI https://doi.org/10.1145/3506860.3506914 Publisher Association for Computing Machinery (ACM) ISBN 978-1-4503-9573-1 Source LAK 2022 - Conference Proceedings: Learning Analytics for Transition, Disruption and Social Change - 12th International Conference on Learning Analytics and Knowledge Event 12th International Conference on Learning Analytics and Knowledge: Learning Analytics for Transition, Disruption and Social Change, LAK 2022, 2022-03-21 → 2022-03-25, Virtual, Online, United States Series ACM International Conference Proceeding Series Part of collection Institutional Repository Document type conference paper Rights © 2022 Mohammad Khalil, L.Y.J. Wong, Erkan Er, Martin Heitmann, Gleb Belokrys Files PDF LAK22_submission_220_JW.pdf 681.22 KB Close viewer /islandora/object/uuid:f6bef77a-2f9b-475e-a44e-f30d6a4e14eb/datastream/OBJ/view