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What is Topic Modeling

Chapter 6
Theoretical and Practical Approaches to Innovation in Higher Education
A popular text mining technique from machine learning and natural language processing study. The term usually refers to a type of statistical model to discover the abstract and latent topics and to identify the hidden semantic structure that occur in media corpus.
Published in Chapter:
What Can College Teachers Learn From Students' Experiential Narratives in Hybrid Courses?: A Text Mining Method of Longitudinal Data
Kenneth C. C. Yang (The University of Texas at El Paso, USA) and Yowei Kang (National Taiwan Ocean University, Taiwan)
Copyright: © 2020 |Pages: 22
DOI: 10.4018/978-1-7998-1662-1.ch006
Abstract
Thanks to the rapid development of asynchronous and synchronous instructional technologies (such as Blackboard and Moodle), many college instructors have flipped their classrooms to create a more student-centered learning environment. The emphasis on cultivating students' life-long learning abilities through the enhancement of information literacy or technology-enabled learning has transformed the pedagogical approaches used by many college instructors. This text mining study was based on a corpus of a three-year experiential narrative collected by the instructor from over 15 college-level courses to identify keywords, main topics/themes, and associations of these topical concepts in students' experiential narratives during and after taking these hybrid classes. QDA Miner text mining software was used to analyze these experiential narratives. Results, implications, and limitations were presented.
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More Results
Chapter 23
Analysis of Online Hotel Reviews During the COVID-19 Pandemic Using Topic Modeling
Topic modeling is an unsupervised machine learning technique that finds natural sets of items and similar expressions by identifying the words that best represent a set of documents.
Published in Chapter: Analysis of Online Hotel Reviews During the COVID-19 Pandemic Using Topic Modeling; From: Handbook of Research on the Impacts and Implications of COVID-19 on the Tourism Industry
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Chapter 7
Using Computational Text Analysis to Explore Open-Ended Survey Question Responses
The extraction of topics within a piece of writing or set of written texts.
Published in Chapter: Using Computational Text Analysis to Explore Open-Ended Survey Question Responses; From: Online Survey Design and Data Analytics: Emerging Research and Opportunities
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Chapter 14
Political Mobilization Strategies in Taiwan's Sunflower Student Movement on March 18, 2014: A Text-Mining Analysis of Cross-National Media Corpus
A popular text mining technique from machine learning and natural language processing research. The term usually refers to a type of statistical model to discover the abstract and latent topics and to identify the hidden semantic structure that occur in media corpus.
Published in Chapter: Political Mobilization Strategies in Taiwan's Sunflower Student Movement on March 18, 2014: A Text-Mining Analysis of Cross-National Media Corpus; From: Using New Media for Citizen Engagement and Participation
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Chapter 9
Analyzing the Evolution of Digital Assessment in Education Literature Using Bibliometrics and Natural Language Processing
A topic model is a type of statistical model for discovering the abstract “topics” that occur in a collection of documents.
Published in Chapter: Analyzing the Evolution of Digital Assessment in Education Literature Using Bibliometrics and Natural Language Processing; From: Handbook of Research on Digital-Based Assessment and Innovative Practices in Education
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Chapter 2
A Bibliometrics and Text Analytics Review of Games and Gamification in Education
A topic model is a type of statistical model for discovering the abstract “topics” that occur in a collection of documents.
Published in Chapter: A Bibliometrics and Text Analytics Review of Games and Gamification in Education; From: Handbook of Research on the Influence and Effectiveness of Gamification in Education
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Chapter 7
Digital Archives and Data Science: Building Programs and Partnerships for Health Sciences Research
A text mining tool used to analyze words in a document (or collection of documents) to discover frequently used terms and to group them into clusters. These clusters can provide insight into the topics of a document or collection, allowing a user to better understand their content without needing to read through thousands or millions of pages.
Published in Chapter: Digital Archives and Data Science: Building Programs and Partnerships for Health Sciences Research; From: Handbook of Research on Academic Libraries as Partners in Data Science Ecosystems
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Chapter 9
Predicting the Future Research Gaps Using Hybrid Approach: Machine Learning and Ontology - A Case Study on Biodiversity
Topic modeling is a tool for unsupervised document classification, analogous to clustering on numeric data, which identifies certain normal classes of things (topics) even though we're not sure what we're searching for. Topic modeling provides tools for arranging, interpreting, scanning, and summarizing broad electronic collections automatically.
Published in Chapter: Predicting the Future Research Gaps Using Hybrid Approach: Machine Learning and Ontology - A Case Study on Biodiversity; From: Handbook of Research on Knowledge and Organization Systems in Library and Information Science
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Chapter 11
Re-Evaluating the Service Quality of Airports After the COVID-19 Pandemic: A Full Consistency Method Approach
It refers to a statistical modeling technique for determining the abstract “themes” that appear in a collection of texts.
Published in Chapter: Re-Evaluating the Service Quality of Airports After the COVID-19 Pandemic: A Full Consistency Method Approach; From: Cases on Traveler Preferences, Attitudes, and Behaviors: Impact in the Hospitality Industry
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