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3 articles for “linguistic minimalism”
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Linguistic Minimalism in Digital Communication: The Shrinking of Language in Hyper-Speed Communication Environments
Abstract: The digital revolution has fundamentally transformed linguistic practices, precipitating what we term "linguistic minimalism"—the systematic reduction of language to essential semantic components in hyper-speed communication environments. This research examines how contemporary digital platforms have catalyzed a contraction in linguistic expression through abbreviations, semantic compression, emoji symbolism, and strategic silence. Drawing on discourse analysis, pragmatics, and social semiotics, this study explores four interconnected dimensions: emojis and GIFs as primary meaning carriers, …
Published in OmniScience: A Multi-disciplinary Journal · Vol. 16, Issue 1, 2026 Read article
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AI-Driven Psychological Profiling on Social Media: Mechanisms, Ethical Breaches, and Regulatory Challenges in Data Inference
Abstract: This literature review examines AI-driven psychological profiling on social media, analyzing 21 academic studies that focus on machine learning techniques such as supervised learning, deep neural networks, sentiment analysis, and natural language processing. These methodologies infer mental health indicators—such as depression, anxiety, and stress—from users' digital footprints, encompassing linguistic patterns, engagement metrics, and temporal behaviors. While these tools offer potential for early detection of psychological distress, they also raise significant …
Published in Recent Trends in Social Studies · Vol. 2, Issue 1, 2025 · pp. 1–7 Read article
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Procedure for Conventional Facial Emotion Detection Algorithms Based on Machine Learning
Abstract: Researchers in psychology, computer science, linguistics, neurology, and allied fields have become more interested in a human-computer interface system for autonomous face recognition or facial expression recognition. This study has recommended an Automatic Facial Expression Recognition System (AFERS). The proposed methodology consists of face detection, feature extraction, and facial expression identification processes. The initial phases of the face detection procedure include skin color identification using the YCbCr color model, illumination …
Published in International Journal of Electronics Automation · Vol. 1, Issue 1, 2023 · pp. 07–13 Read article