Reddit Sentiment Analysis on the Impact of AI Using VADER, TextBlob, and BERT

This paper investigates public sentiment on the future impact of artificial intelligence (AI) by analysing Reddit data using lexicon-based sentiment analysers and a machine learning approach. The study utilizes data from a manually selected subreddit to ensure the dataset’s relevance while reducing noise to improve sentiment results. Sentiment analysis was conducted using VADER, TextBlob, and BERT, which provided scores indicating negative, neutral, or positive polarity. Data preprocessing involved stop word removal to enhance model performance. Results were visualized using WordCloud and Matplotlib graphs including histograms, bar graphs, and pie charts to compare sentiment distributions across the different analysers. The findings reveal varied public opinions on AI’s future, as well as a discrepancy between the models. From 559 comments, VADER reported 23% negative, 22% neutral, and 55% positive sentiments; TextBlob found 16% negative, 37% neutral, and 47% positive sentiments; and BERT indicated 42% negative, 28% neutral, and 30% positive sentiments. Notably, the overall public opinion on AI’s future impact was positive, albeit with variances across sentiment analysers. This study highlights the discrepancies between different sentiment analysis tools and underscores the need for further comparative research.

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Publication Details

Journal
Procedia Computer Science
Published
2025-01-01
DOI
https://doi.org/10.1016/j.procs.2025.04.326
Citations
3
Primary Topic
Sentiment Analysis and Opinion Mining
Type
article
Field-Weighted Citation Impact
7.44
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article

Reddit Sentiment Analysis on the Impact of AI Using VADER, TextBlob, and BERT

Khanh Do-Cong Pham, Krishna Chaitanya Rao Kathala, Shashank Palakurthi
3 citations
Procedia Computer Science
Sentiment Analysis and Opinion Mining
7.44
article

Reddit Sentiment Analysis on the Impact of AI Using VADER, TextBlob, and BERT

Khanh Do-Cong Pham, Krishna Chaitanya Rao Kathala, Shashank Palakurthi
article en
3 citations

Abstract

This paper investigates public sentiment on the future impact of artificial intelligence (AI) by analysing Reddit data using lexicon-based sentiment analysers and a machine learning approach. The study utilizes data from a manually selected subreddit to ensure the dataset’s relevance while reducing noise to improve sentiment results. Sentiment analysis was conducted using VADER, TextBlob, and BERT, which provided scores indicating negative, neutral, or positive polarity. Data preprocessing involved stop word removal to enhance model performance. Results were visualized using WordCloud and Matplotlib graphs including histograms, bar graphs, and pie charts to compare sentiment distributions across the different analysers. The findings reveal varied public opinions on AI’s future, as well as a discrepancy between the models. From 559 comments, VADER reported 23% negative, 22% neutral, and 55% positive sentiments; TextBlob found 16% negative, 37% neutral, and 47% positive sentiments; and BERT indicated 42% negative, 28% neutral, and 30% positive sentiments. Notably, the overall public opinion on AI’s future impact was positive, albeit with variances across sentiment analysers. This study highlights the discrepancies between different sentiment analysis tools and underscores the need for further comparative research.

Procedia Computer ScienceVol. 258
Christian Brothers University (US), University of Massachusetts Amherst (US), The University of Texas at Austin (US)
Openalex Percentile: Top 3%
Sentiment Analysis and Opinion Mining
7.44
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Reddit Sentiment Analysis on the Impact of AI Using VADER, TextBlob, and BERT — Khanh Do-Cong Pham, Krishna Chaitanya Rao Kathala, et al. · Procedia Computer Science (2025) | TGRS Research Map | TGRS