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A systematic review of the use of topic models for short text social media analysis

Recently, research on short text topic models has addressed the challenges of social media datasets. These models are typically evaluated using automated measures. However, recent work suggests that these evaluation measures do not inform whether the topics produced can yield meaningful insights for...

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Autores principales: Laureate, Caitlin Doogan Poet, Buntine, Wray, Linger, Henry
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Netherlands 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10150353/
https://www.ncbi.nlm.nih.gov/pubmed/37362887
http://dx.doi.org/10.1007/s10462-023-10471-x
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author Laureate, Caitlin Doogan Poet
Buntine, Wray
Linger, Henry
author_facet Laureate, Caitlin Doogan Poet
Buntine, Wray
Linger, Henry
author_sort Laureate, Caitlin Doogan Poet
collection PubMed
description Recently, research on short text topic models has addressed the challenges of social media datasets. These models are typically evaluated using automated measures. However, recent work suggests that these evaluation measures do not inform whether the topics produced can yield meaningful insights for those examining social media data. Efforts to address this issue, including gauging the alignment between automated and human evaluation tasks, are hampered by a lack of knowledge about how researchers use topic models. Further problems could arise if researchers do not construct topic models optimally or use them in a way that exceeds the models’ limitations. These scenarios threaten the validity of topic model development and the insights produced by researchers employing topic modelling as a methodology. However, there is currently a lack of information about how and why topic models are used in applied research. As such, we performed a systematic literature review of 189 articles where topic modelling was used for social media analysis to understand how and why topic models are used for social media analysis. Our results suggest that the development of topic models is not aligned with the needs of those who use them for social media analysis. We have found that researchers use topic models sub-optimally. There is a lack of methodological support for researchers to build and interpret topics. We offer a set of recommendations for topic model researchers to address these problems and bridge the gap between development and applied research on short text topic models. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10462-023-10471-x.
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spelling pubmed-101503532023-05-02 A systematic review of the use of topic models for short text social media analysis Laureate, Caitlin Doogan Poet Buntine, Wray Linger, Henry Artif Intell Rev Article Recently, research on short text topic models has addressed the challenges of social media datasets. These models are typically evaluated using automated measures. However, recent work suggests that these evaluation measures do not inform whether the topics produced can yield meaningful insights for those examining social media data. Efforts to address this issue, including gauging the alignment between automated and human evaluation tasks, are hampered by a lack of knowledge about how researchers use topic models. Further problems could arise if researchers do not construct topic models optimally or use them in a way that exceeds the models’ limitations. These scenarios threaten the validity of topic model development and the insights produced by researchers employing topic modelling as a methodology. However, there is currently a lack of information about how and why topic models are used in applied research. As such, we performed a systematic literature review of 189 articles where topic modelling was used for social media analysis to understand how and why topic models are used for social media analysis. Our results suggest that the development of topic models is not aligned with the needs of those who use them for social media analysis. We have found that researchers use topic models sub-optimally. There is a lack of methodological support for researchers to build and interpret topics. We offer a set of recommendations for topic model researchers to address these problems and bridge the gap between development and applied research on short text topic models. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10462-023-10471-x. Springer Netherlands 2023-05-01 /pmc/articles/PMC10150353/ /pubmed/37362887 http://dx.doi.org/10.1007/s10462-023-10471-x Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Laureate, Caitlin Doogan Poet
Buntine, Wray
Linger, Henry
A systematic review of the use of topic models for short text social media analysis
title A systematic review of the use of topic models for short text social media analysis
title_full A systematic review of the use of topic models for short text social media analysis
title_fullStr A systematic review of the use of topic models for short text social media analysis
title_full_unstemmed A systematic review of the use of topic models for short text social media analysis
title_short A systematic review of the use of topic models for short text social media analysis
title_sort systematic review of the use of topic models for short text social media analysis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10150353/
https://www.ncbi.nlm.nih.gov/pubmed/37362887
http://dx.doi.org/10.1007/s10462-023-10471-x
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