AI in the Public Eye: A Comprehensive Sentiment Analysis of Public Opinion Toward Artificial Intelligence on Social Media Platforms.

Abstract

Artificial Intelligence (AI) is a rapidly evolving technology with far-reaching implications, and it has sparked intense public discussion on social media platforms. This study conducts a comprehensive sentiment analysis of AI-related posts on Twitter, YouTube, and Reddit from 2017 to 2024, aiming to evaluate public perceptions and attitudes toward AI. Approximately 133,004 social media posts were analysed using a fine-tuned RoBERTa model for sentiment classification, along with Latent Dirichlet Allocation (LDA), n-gram analysis, and word co-occurrence mapping for topic modelling. The findings reveal that a considerable portion of social media users express negative sentiments towards AI (46.09%), followed by neutral sentiments (39.29%) and positive sentiments (14.62%). LDA analysis identified 20 distinct topics, including AI ethics, job impacts, and philosophical implications. Temporal analysis revealed a notable increase in AI-related discourse starting in 2022, accompanied by evolving sentiment patterns. The results reveal a complex landscape of public perception regarding AI, characterised by ongoing concerns about its societal impacts, coupled with a growing interest in the AI's technical aspects. Future research could explore cross-cultural perceptions of AI and examine how direct interactions with AI systems influence public attitudes.

Divisions: College of Engineering & Physical Sciences > School of Computer Science and Digital Technologies > Software Engineering & Cybersecurity
Additional Information: This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (https://creativecommons.org/licenses/by-nc-nd/4.0/).
Event Title: The Second UK AI Conference 2024
Event Type: Other
Event Location: University of Birmingham
Event Dates: 2024-11-22 - 2024-11-22
Last Modified: 01 Apr 2025 07:12
Date Deposited: 17 Dec 2024 10:16
PURE Output Type: Poster
Published Date: 2024-11-22
Authors: Appiah, Ezekiel
Htait, Amal (ORCID Profile 0000-0003-4647-9996)

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