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A Seed-Guided Latent Dirichlet Allocation Approach to Predict the Personality of Online Users Using the PEN Model
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In: Algorithms; Volume 15; Issue 3; Pages: 87 (2022)
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| 2 |
Explorando la ciberviolencia contra mujeres y niñas en Filipinas a través de Mining Online News
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In: Comunicar: Revista científica iberoamericana de comunicación y educación, ISSN 1134-3478, Nº 70, 2022 (Ejemplar dedicado a: Nuevos retos del profesorado ante la enseñanza digital), pags. 125-138 (2022)
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Topic models do not model topics: epistemological remarks and steps towards best practices
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In: EISSN: 2416-5999 ; Journal of Data Mining and Digital Humanities ; https://hal.archives-ouvertes.fr/hal-03261599 ; Journal of Data Mining and Digital Humanities, Episciences.org, 2021, 2021, ⟨10.46298/jdmdh.7595⟩ (2021)
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| 4 |
Characterizing Topics in Social Media Using Dynamics of Conversation
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In: Entropy; Volume 23; Issue 12; Pages: 1642 (2021)
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| 5 |
Digital Humanities - A Discipline in its Own Right? An Analysis of the Role and Position of DH in the Academic Landscape ...
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Digital Humanities - A Discipline in its Own Right? An Analysis of the Role and Position of DH in the Academic Landscape ...
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| 7 |
Exploring Online Depression Forums via Text Mining: A Comparison of Reddit and a Curated Online Forum ...
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| 8 |
Same same, but different ? On the Relation of Information Science and the Digital Humanities A Scientometric Comparison of Academic Journals Using LDA and Hierarchical Clustering ...
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| 9 |
LDA-Based Topic Modeling Sentiment Analysis Using Topic/Document/Sentence (TDS) Model
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In: Applied Sciences ; Volume 11 ; Issue 23 (2021)
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Abstract:
Customer reviews on the Internet reflect users&rsquo ; sentiments about the product, service, and social events. As sentiments can be divided into positive, negative, and neutral forms, sentiment analysis processes identify the polarity of information in the source materials toward an entity. Most studies have focused on document-level sentiment classification. In this study, we apply an unsupervised machine learning approach to discover sentiment polarity not only at the document level but also at the word level. The proposed topic document sentence (TDS) model is based on joint sentiment topic (JST) and latent Dirichlet allocation (LDA) topic modeling techniques. The IMDB dataset, comprising user reviews, was used for data analysis. First, we applied the LDA model to discover topics from the reviews ; then, the TDS model was implemented to identify the polarity of the sentiment from topic to document, and from document to word levels. The LDAvis tool was used for data visualization. The experimental results show that the analysis not only obtained good topic partitioning results, but also achieved high sentiment analysis accuracy in document- and word-level sentiment classifications.
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Keyword:
polarity detection; sentiment analysis; sentiment classification; topic modeling
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URL: https://doi.org/10.3390/app112311091
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| 10 |
Real-Time Infoveillance of Moroccan Social Media Users’ Sentiments towards the COVID-19 Pandemic and Its Management
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In: International Journal of Environmental Research and Public Health ; Volume 18 ; Issue 22 (2021)
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| 11 |
Schizophrenia Detection Using Machine Learning Approach from Social Media Content
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In: Sensors ; Volume 21 ; Issue 17 (2021)
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| 12 |
Exploring Latent Topics and Research Trends in Mathematics Teachers’ Knowledge Using Topic Modeling: A Systematic Review
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In: Mathematics ; Volume 9 ; Issue 22 (2021)
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| 13 |
Relationship Between Poetic Meter and Meaning in Accentual-Syllabic Verse (data and replication code) ...
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| 14 |
Relationship Between Poetic Meter and Meaning in Accentual-Syllabic Verse (data and replication code) ...
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| 15 |
Relationship Between Poetic Meter and Meaning in Accentual-Syllabic Verse (data and replication code) ...
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| 16 |
Jeu vidéo et linéarité romanesque ... : La structure Aventure/mésaventures dans Dragon Age : Origins ...
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| 18 |
Ensemble Topic Modeling using Weighted Term Co-associations
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| 19 |
Examining the Social Media Antecedents of Racial Justice: Evidence from Twitter
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| 20 |
EXPLORING PSEUDO-TOPIC-MODELING FOR CREATING AUTOMATED DISTANT-ANNOTATION SYSTEMS
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In: Theses (2021)
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