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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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Abstract:
There is a growing interest in topic modeling to decipher the valuable information embedded in natural texts. However, there are no studies training an unsupervised model to automatically categorize the social networks (SN) messages according to personality traits. Most of the existing literature relied on the Big 5 framework and psychological reports to recognize the personality of users. Furthermore, collecting datasets for other personality themes is an inherent problem that requires unprecedented time and human efforts, and it is bounded with privacy constraints. Alternatively, this study hypothesized that a small set of seed words is enough to decipher the psycholinguistics states encoded in texts, and the auxiliary knowledge could synergize the unsupervised model to categorize the messages according to human traits. Therefore, this study devised a dataless model called Seed-guided Latent Dirichlet Allocation (SLDA) to categorize the SN messages according to the PEN model that comprised Psychoticism, Extraversion, and Neuroticism traits. The intrinsic evaluations were conducted to determine the performance and disclose the nature of texts generated by SLDA, especially in the context of Psychoticism. The extrinsic evaluations were conducted using several machine learning classifiers to posit how well the topic model has identified latent semantic structure that persists over time in the training documents. The findings have shown that SLDA outperformed other models by attaining a coherence score up to 0.78, whereas the machine learning classifiers can achieve precision up to 0.993. We also will be shared the corpus generated by SLDA for further empirical studies.
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Keyword:
machine learning; PEN model; personality detection; topic modeling
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URL: https://doi.org/10.3390/a15030087
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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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| 3 |
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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| 6 |
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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| 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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