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Locating Loneliness Through Social Intelligence Analysis.

Hurmat Ali Shah1, Mowafa Househ1

  • 1College of Science and Engineering, Hamad Bin Khalifa University, Doha, Qatar.

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Summary
This summary is machine-generated.

This study introduces a global loneliness map using social media data to understand loneliness dynamics. Analyzing US tweets with sentiment analysis reveals psychosocial factors linked to loneliness.

Keywords:
Lonelinesssentiment analysissocial intelligence analysissocial mediatwitter analysis

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Area of Science:

  • Public Health
  • Computational Social Science
  • Psychology

Background:

  • Loneliness is a significant global public health concern.
  • The dynamics and contributing factors of loneliness remain poorly understood.
  • Social intelligence analysis offers a novel approach to study subjective experiences like loneliness.

Purpose of the Study:

  • To present the first proof of concept for a global loneliness map.
  • To analyze social media data for understanding the dynamics of loneliness.
  • To identify associations between loneliness and socioeconomic/emotional themes.

Main Methods:

  • Collected and analyzed social media data (tweets) from the USA using loneliness-associated keywords.
  • Employed Natural Language Processing (NLP) with a Valence Aware Dictionary for Sentiment Reasoning (VADER) for sentiment analysis.
  • Performed psychosocial linguistic feature analysis on negatively-sentimental tweets to correlate themes with loneliness.

Main Results:

  • Demonstrated the feasibility of using social media data for loneliness research.
  • Identified meaningful associations between themes and loneliness.
  • Highlighted the potential of machine learning tools in understanding subjective experiences.

Conclusions:

  • Social intelligence analysis via social media provides a valuable tool for understanding loneliness.
  • The global loneliness map concept shows promise for future research.
  • Further analysis can uncover deeper correlations between psychosocial factors and loneliness.