Loneliness Detection from Social Media: A Text Analytics Approach
Files
Date
2025-01-07
Contributor
Advisor
Department
Instructor
Depositor
Speaker
Researcher
Consultant
Interviewer
Narrator
Transcriber
Annotator
Journal Title
Journal ISSN
Volume Title
Publisher
Volume
Number/Issue
Starting Page
3769
Ending Page
Alternative Title
Abstract
In an era where digital interactions significantly influence our social interactions, understanding how loneliness is expressed online becomes paramount. This study delves into the linguistic representation of loneliness on Reddit, utilizing techniques in natural language processing (NLP) and machine learning. By employing frequency-based, similarity-based, and association-based methods, a unified lexicon was generated, demonstrating promising performance in classifying loneliness-related posts. The identification and validation of 536 most impactful entries from this lexicon underscore their predictive power and genuine relevance as markers of loneliness. This research advances our comprehension of loneliness within digital contexts and underscores the potential of computational methods in detecting and addressing loneliness online. The identified lexicon lays the groundwork for AI-driven mental health interventions, underscoring the significance of language in understanding and addressing loneliness in the digital age.
Description
Keywords
Actors, Agents, and Avatars: Visualizing Digital Humans in E-Commerce and Social Media, design science, healthcare, lexicon, loneliness, machine learning, nlp
Citation
Extent
8
Format
Geographic Location
Time Period
Related To
Proceedings of the 58th Hawaii International Conference on System Sciences
Related To (URI)
Table of Contents
Rights
Attribution-NonCommercial-NoDerivatives 4.0 International
Rights Holder
Local Contexts
Email libraryada-l@lists.hawaii.edu if you need this content in ADA-compliant format.