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Showing 1 to 20 of 136 for “"topic modeling"”.
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Topic modeling in game reviews
… game reviews for Elden Ring were analyzed for topic modelling using Latent Dirichlet Allocation (LDA), Bidirectional Encoder Representations from Transformers (BERT), and a hybrid model combining both to identify effective methods for extracting underlying themes in player feedback. We analyzed …
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Topic Modeling Location-Based Social Media Applications
<p>Topic modeling is a technique used in text analysis and mining across various research domains. The number of social media applications and users is increasing daily, and analyzing these data streams provides added value, relevance, and significance for both scholarly and practitioner …
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Automatic detection of research interest using topic modeling
… research papers written by him or her, using a topic model learned from a corpus of research paper text not necessarily related to any faculty members of MIT, and a list of topic keywords such as that of the Library of Congress. The topic model was generated using a variant of Latent Dirichlet …
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Expressive Forms of Topic Modeling to Support Digital Humanities
… a need to structure this massive amount of data. Topic modeling is one of the most used techniques for analyzing and understanding the latent structure of large text collections. Probabilistic graphical models are the main building block behind topic modeling and they are used to express …
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Topic Modeling for Inferring Brain States from Electroencephalography (EEG) Signals
… state of the brain. We explore the use of topic modeling – which are popular text processing algorithms – to infer brain states from EEG signals. Latent Dirichlet allocation (LDA) is our preferred topic model because of its mixture-of-mixtures nature and its ability to be trained in an …
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Exploring Topic Modeling in The Domain of Integrated Water Resource Management
… application of text mining techniques, namely, topic modelling, to scientific publications in the sustainable water resource management domain with the goal to identify major research questions, practical problems and methodological approaches used to address these problems. Comparative analysis …
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Topic Modeling for Heterogeneous Digital Libraries: Tailored Approaches Using Large Language Models
… terminology, making achieving clear and coherent topic representations challenging. Existing topic modeling techniques often struggle with such heterogeneous collections, leaving a gap in providing interpretable and meaningful topic labels. This thesis addresses these challenges through a …
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COP TOPICS: TOPIC MODELING-ASSISTED DISCOVERIES OF POLICE-RELATED THEMES IN AFRICAN-AMERICAN JOURNALISTIC TEXTS
… with computerized text analysis tools like topic modeling software to aid them in their content analyses. This thesis considers to what degree topic modeling software can be used at the exploratory stage of designing a content analysis study to aid in uncovering themes and variables worthy …
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Sentiment analysis of product reviews using coupled sentence-bidirectional encode representations from transformers and topic modeling
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2024-09-16 without embargo terms
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Profile Creation with Topic Modeling and Semantic Analysis from Conversations about COVID-19 among U.S. Older Adults
… process, we propose an approach for automated topic extraction with sentiment analysis using a natural language processing technique known as topic modeling. While automated methods for quantitative data are common, methods for qualitative data, especially focus group text, have not been …
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Data-Driven Assessment of Digital Age Inclusion: Topic Modeling Seoul’s Digital Governance Platform to Evaluate Elderly Representation
This paper examines the intersection of population aging and digital civic government in Seoul, South Korea. As cities worldwide digitize and age simultaneously, understanding elderly citizens' representation in digital governance platforms becomes critical for inclusive urban governance. As a …
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Understanding consumer engagement with vertical farming brands on Twitter: An approach of guided Latent Dirichlet Allocation for topic modeling
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2023-12-04 without embargo terms
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The nature of the human resource development research–practice gap: Text data mining and topic modeling analysis of three decades of professional and academic literature from 1990 to 2022
… quantitative descriptive analysis to explore topic representation and the change in topic prevalence over time in both professional and academic HRD journals. Utilizing structural topic modeling (STM) and a 50/50 training–test dataset split approach, this study scrutinizes latent topics and …
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Summarizing Developer Chat Conversations
… is an attempt to tackle this problem by applying topic modeling techniques to generate discussion summaries. We use a dataset extracted from the Discord chat conversations and evaluate four topic modeling techniques to identify the primary topics discussed. We evaluate different embedding models …
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Advancing semantic modeling: addressing coordination, interpretability, and data scarcity in domain representation
… from unorganized information. Traditional topic models provide a powerful framework for discovering latent themes but often fall short in practice: their outputs are generic and difficult to interpret, alignment across corpora is not guaranteed, and they struggle with both short documents …
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Second chance competitive autoencoders for understanding textual data
… to each text. Dimensionality reduction and topic modeling in Mining text data has received a lot of attention. Topic modeling is a statistical technique for revealing the underlying semantic structure in a large collection of documents. Applying conventional autoencoders on textual data …
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Exploring a New Conceptual Framework in Aviation Maintenance Incident Reporting Using Natural Language Processing
… to implement Latent Dirichlet Allocation in a topic modeling strategy. The topic modeling process distilled these reports into a set of topic word groups that reflect the prevalent themes within the corpus of documents, allowing for a reasonable effort of evaluation by subject matter experts. …
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