Reddit Sentiment Analysis on the Impact of AI Using VADER, TextBlob, and BERT
Kristi Pham, Krishna Chaitanya Rao Kathala, Shashank Palakurthi
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.