Social Media Data Mining With Natural Language Processing on Public Dream Contents

TL;DR

This study analyzes Reddit dream content to assess psychological impacts of COVID-19, using NLP techniques including fine-tuned language models for sentiment analysis, revealing changes in subconscious responses during the pandemic.

Contribution

It introduces a novel approach combining social media data with NLP and fine-tuned models to study mental health impacts of COVID-19 through dream content analysis.

Findings

Shift in dream sentiment from positive to negative post-pandemic

Effective fine-tuning of LLaMA 3.1-8B for sentiment classification

Insights into subconscious psychological effects during COVID-19

Abstract

The COVID-19 pandemic has significantly transformed global lifestyles, enforcing physical isolation and accelerating digital adoption for work, education, and social interaction. This study examines the pandemic's impact on mental health by analyzing dream content shared on the Reddit r/Dreams community. With over 374,000 subscribers, this platform offers a rich dataset for exploring subconscious responses to the pandemic. Using statistical methods, we assess shifts in dream positivity, negativity, and neutrality from the pre-pandemic to post-pandemic era. To enhance our analysis, we fine-tuned the LLaMA 3.1-8B model with labeled data, enabling precise sentiment classification of dream content. Our findings aim to uncover patterns in dream content, providing insights into the psychological effects of the pandemic and its influence on subconscious processes. This research highlights the profound changes in mental landscapes and the role of dreams as indicators of public well-being during unprecedented times.