Analyzing Large Collections of Open-Ended Feedback From MOOC Learners Using LDA Topic Modeling and Qualitative Analysis

Nanda, Gaurav; Douglas, Kerrie A.; Waller, David R.; Merzdorf, Hillary E.; Goldwasser, Dan

doi:10.1109/tlt.2021.3064798

Cited by 39 publications

(14 citation statements)

References 26 publications

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“…The Overall Topical Patterns Repeated modeling with topic numbers ranging from 3 to 26 on the corpus suggests that the optimized topic numbers in the US and Chinese reports are both 20, with the "Cv" coherence scores being 0.54 and 0.51, respectively. According to findings in some previous research (e.g., Nanda et al, 2021;Röder et al, 2015;Syed & Spruit, 2017), a "Cv" coherence score equals 0.50 or above is more likely to efficiently reflect the topical structure of the corpus under investigation. Based on their attached keywords, each topic is given a label that could properly summarize its topical theme.…”

Section: Resultsmentioning

confidence: 87%

Agenda-Setting in Cross-National Coverage of COVID-19: An Analysis of Elite Newspapers in US and China with Topic Modeling

2021

ONLINE J. COMMUN. MEDIA TECHNOL

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This study examines agenda-setting in US-China elite newspapers coverage of COVID-19 through topic modeling. It attempts to contribute to studies of media agenda first by demonstrating the relevance of text-mining in agenda-setting research and second by comparing how elite newspapers from different countries choose topics as part of agenda-setting when they report a single event. Topic-modeling the news corpora collected between 15 January 2020 and 15 June 2020 from the four US-China elite newspapers, the study finds that "domestic economy" and "international relations" are the two dominant topics that help shape the agenda in the Chinese newspapers, whereas "family & friends" and "daily life" are the topics playing the same role in the US newspapers. The study argues that such differences may associate with ideological gaps between the two countries in terms of "concepts of development", "media bias" and "views of individualism".

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Section: Resultsmentioning

confidence: 87%

Agenda-Setting in Cross-National Coverage of COVID-19: An Analysis of Elite Newspapers in US and China with Topic Modeling

2021

ONLINE J. COMMUN. MEDIA TECHNOL

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“…LDA is an unsupervised machine learning technique that utilizes a probabilistic graph model 23 . It determines and extracts words based on the contextual probability of words within documents and possesses certain empirical characteristics.…”

Section: Methodsmentioning

confidence: 99%

Metricizing policy texts: Comprehensive dataset on China’s Agri-policy intensity spanning 1982–2023

Wu,

Wang,

et al. 2024

Sci Data

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Due to the lack of direct assessment metrics, existing studies on the intensity of agricultural policies often utilize indicators such as Gross Domestic Product (GDP) of agriculture or the quantity of agricultural policies as measures. Optimizing methods for analyzing the intensity of agricultural policies will significantly impact parameter selection in agricultural policy research and the evaluation of policy effectiveness. In this study, we constructed a Chinese Agricultural Policy Corpus using agricultural policies released by various governmental agencies at the national level in China from 1982 to April 2023. We quantified the values of agricultural domain terms in the corpus and evaluated the intensity of each agricultural policy document. The validation results of this study indicate a strong correlation between the intensity of agricultural policies and agricultural GDP. The trend in agricultural GDP changes lags behind policy intensity by 2.5 years (at a 95% confidence level), thus validating the rationality of our constructed corpus, agricultural policy scoring dataset, and methodology.

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“…To provide answers to RQ2 which addresses education blockchain infrastructure, technologies and methods, we conducted a content analysis on all the 468 records. First, we excluded 5 entries with missing abstracts and performed topic modelling with the abstract data using LDA as used in some previous studies [40], [41]. To obtain the optimal number of topics to classify the abstract data, we calculated the topic coherence score [42] for various models while changing the number of topics: starting at 2 topics to 50 topics in steps of 6.…”

Section: Content Analysis For Case Studymentioning

confidence: 99%

Blockchain in Education: A Systematic Review and Practical Case Studies

et al. 2022

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The advent of blockchain technology over the last decade has led to the development of multiple use-cases of decentralization in various fields including education. This paper presents a unique bibliometric and qualitative analysis of the blockchain in education with novel contributions on temporal development, emerging themes and practical case studies on adoption and integration with existing educational technologies. We focus on identifying the major actors in the space, demographic participation and adoption, current hot topics, grey areas, and potential areas for innovation. Our analysis shows that while the blockchain has been around for about 13 years, blockchain in education only became prominent 5 years ago. This research also reveals that most of the efforts have been focused on reporting and verifying academic certificates and transcripts: only very few research focused on reporting and connecting in-depth academic records such as learning behaviour logs, learning contents and assessment data. This calls for concern as current education blockchain systems do not consider interoperability at the blockchain level and the heterogeneous nature in which institutes create and consume academic data. Finally, we present discussions on the implications of our findings, potential solutions and aspects of education blockchain research that can help to improve educational outcomes for various stakeholders.INDEX TERMS Academic records, analysis, application programming interface (API), artificial intelligence (AI), bibliometric, blockchain of learning logs (BOLL), education, experience API (xAPI), information and communication technology (ICT), latent dirichlet allocation (LDA), learning management system (LMS), learning record store (LRS), learning tools interoperability (LTI), quick response (QR), sharable content object reference model (SCORM), smart ecosystem for learning and inclusion (SELI)

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Analyzing Large Collections of Open-Ended Feedback From MOOC Learners Using LDA Topic Modeling and Qualitative Analysis

Cited by 39 publications

References 26 publications

Agenda-Setting in Cross-National Coverage of COVID-19: An Analysis of Elite Newspapers in US and China with Topic Modeling

Agenda-Setting in Cross-National Coverage of COVID-19: An Analysis of Elite Newspapers in US and China with Topic Modeling

Metricizing policy texts: Comprehensive dataset on China’s Agri-policy intensity spanning 1982–2023

Blockchain in Education: A Systematic Review and Practical Case Studies

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