A Comparison of Neural Word Embedding Language Models for Classifying Social Media Users in the Healthcare Context

Article Computer Science, Artificial Intelligence

Prototype Theory Meets Word Embedding: A Novel Approach for Text Categorization via Granular Computing

Enrico De Santis et al.

Summary: This paper presents a novel framework for solving text categorization tasks using the Conceptual Space Theory, Granular Computing approach, and Machine Learning. The authors propose a concept-based representation of text and compare the performance of neural embedding techniques and LSA in knowledge discovery applications.

COGNITIVE COMPUTATION (2023)

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Article Computer Science, Artificial Intelligence

Multifractal Characterization of Texts for Pattern Recognition: On the Complexity of Morphological Structures in Modern and Ancient Languages

Enrico De Santis et al.

Summary: This study applies an interdisciplinary approach to analyze the complexity underlying the morphological organization in various linguistic texts and investigates the predictive power of multifractal signatures through machine learning. The results demonstrate the presence of persistence in the analyzed texts, which plays a role in characterizing different linguistic families. The proposed approach is effective and can be used for further comparative studies and advancements in information retrieval and artificial intelligence.

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2023)

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Article Information Science & Library Science

An exploration of how fake news is taking over social media and putting public health at risk

Salman Bin Naeem et al.

Summary: Recent statistics show that the coronavirus has caused almost 250,000 deaths and affected 4 million people. Concerns have been raised about the spread of misinformation during the pandemic. A small study aimed to identify the types and sources of COVID-19 misinformation, revealing the widespread dissemination of fake news on social media.

HEALTH INFORMATION AND LIBRARIES JOURNAL (2021)

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