Identifying learners’ topical interests from social media content to enrich their course preferences in MOOCs using topic modeling and NLP techniques

Zankadi, Hajar; Idrissi, Abdellah; Daoudi, Najima; Hilal, Imane

doi:10.1007/s10639-022-11373-1

Cited by 24 publications

(3 citation statements)

References 42 publications

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“…As far as the authors are concerned, there are no previous studies using BERTopic to model topics in medical literature, the most common uses for BERTopic have been limited to analyzing different topics across social media and other media platforms. [12][13][14] BERTopic and traditional methods (LDA for example) are two different approaches to topic modeling. While LDA has been the traditional method of topic modeling for many years, BERT is a more recent approach and one of the goals of our study was to assess how effective it is in the context of medical literature.…”

Section: Discussionmentioning

confidence: 99%

Assessment of Topics Published in Leading Medical Journals Using Natural Language Processing

Alryalat,

Qasem,

Albdour

et al. 2023

HYMR

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Introduction: Topic detection can be used to identify trends in literature, providing valuable insight into the direction of the field. We developed a natural language processing (NLP) based method to identify topics from given abstracts and assessed the main topics of published articles by top medical journals in the last three years. Methods: This study utilized a two-part methodology to extract and classify original articles published by four non-specialized medical journals; Lancet, New England Journal of Medicine, Journal of the American Medical Association, and British Medical Journal. The first part employed bibliometric data collection to search for original articles published between 2020 and 2022. The second part used an NLP approach based on the BERTopic model to classify the articles included into separate topics. Results: The model was able to classify 1,540 articles out of the included 2,081 (79.42%) into 39 different topics in 11 fields. COVID-19-related and cancer treatment-related articles constituted approximately 25% and 7% of all published papers during 2020-2022 respectively. The study found that each of the included general medical journal tended to focus on certain topics more than others. Conclusion: We identified a new methodology that can identify topics discussed in medical literature from abstracts as an input. We also demonstrated the potential of this methodology for analyzing trends in medical literature more efficiently and effectively. This study's methodology can be replicated on a larger scale with more papers, more journals, and over a longer period, highlighting the importance of further research using NLP models.

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Section: Discussionmentioning

confidence: 99%

Assessment of Topics Published in Leading Medical Journals Using Natural Language Processing

Alryalat,

Qasem,

Albdour

et al. 2023

HYMR

View full text Add to dashboard Cite

show abstract

“…It consists of three steps: UMAP dimensionality reduction, HDBSCAN clustering, and c-TF-IDF extraction of subject terms. Therefore, it is able to take into account the semantic information of the text more fully than the LDA model [21].…”

Section: Bertopic Modelmentioning

confidence: 99%

Identification of Product Innovation Path Incorporating the FOS and BERTopic Model from the Perspective of Invalid Patents

Zhang,

Wu,

Liu

et al. 2023

Applied Sciences

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Under the premise of resource constraint, it is crucial to identify the product innovation opportunities contained in failed patents through external search in order to compensate for the shortcomings of enterprises’ own technology. Due to the cost of patent research and development and the risk of infringement, this paper constructs a product innovation identification path that integrates the FOS and BERTopic model from the perspective of invalid patents. The path consists of three stages, including the identification of the problem to be solved by the product based on functional analysis, the extraction of the subject matter elements based on the core failed patent technology, and the generation and evaluation of innovative solutions based on TRIZ theory and the best- worst method (BWM). Finally, the feasibility of the path constructed in this paper is verified by taking a slurry pump as an example. The application results show that the product innovation identification path constructed in this paper can provide theoretical support for enterprises to carry out technological innovation activities efficiently.

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“…The interconnectedness of media content preferences and the value orientation of the prospective teachers plays an important role in the quality of teaching. (Zankadi et al, 2022) stated that learners interact freely and voluntarily with various forms of user-generated content that conceals their true interests and preferences. Hence, understanding the media content preferences and the value orientation of the prospective teachers can help college instructors in improving their strategies to make it engaging that it catches their interests.…”

Section: Relationship Between Media Content Preferences and Perceptio...mentioning

confidence: 99%

Media Content Preferences and Perceptions Towards Dominant Value Orientations in Media Among Pre-Service Teachers

Mata,

Handang,

Joe

et al. 2023

JPP

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Media Content Preferences and Perceptions towards Dominant Value Orientations in Media Among Pre-Service Teachers. Objective: The purpose of this study was to determine the media content preferences and the perceptions towards dominant value orientations in media. Methods: This research employed a quantitative research design through the use of an online survey technique. Findings: The findings showed that there are gender differences in relation to the pre-service teachers' thematic content preferences. In terms of the preferable television program content and the gender of pre-service teachers, it revealed a statistically significant difference. A positive and negative correlation was also shown between the pre-service teachers' viewing habits and their perceptions of dominant values that are presented in various television programs, and in the pre-service teachers' preferences for music genres and the values promoted in several music videos. Conclusion: The findings in this study indicate that the media content preferences of pre-service teachers differ from their perception of media values.

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Identifying learners’ topical interests from social media content to enrich their course preferences in MOOCs using topic modeling and NLP techniques

Cited by 24 publications

References 42 publications

Assessment of Topics Published in Leading Medical Journals Using Natural Language Processing

Assessment of Topics Published in Leading Medical Journals Using Natural Language Processing

Identification of Product Innovation Path Incorporating the FOS and BERTopic Model from the Perspective of Invalid Patents

Media Content Preferences and Perceptions Towards Dominant Value Orientations in Media Among Pre-Service Teachers

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