AI in the Public Eye: Analysing Social Media Sentiment and Opinion on Artificial Intelligence

Ezekiel Appiah, Amal Htait
Proceedings of the UK AI Conference 2024, PMLR 295:1-15, 2025.

Abstract

Artificial Intelligence (AI), a rapidly evolving technology with far-reaching implications, has become a widely discussed topic on social media platforms. This study conducted a comprehensive sentiment analysis of posts discussing AI topics on Twitter, YouTube and Reddit from 2017 to 2024 to evaluate public perceptions and attitudes toward AI. A total of 133,004 social media posts were analysed using a fine-tuned RoBERTa model for sentiment classification, alongside Latent Dirichlet Allocation (LDA), n-gram, and word co-occurrence mapping for topic modelling. The analysis revealed that 46.09% of the posts express negative sentiments about AI, followed by 39.29% neutral and 14.62% positive sentiments. LDA uncovered 20 key topics, including AI ethics, job impacts, and philosophical implications. Temporal analysis revealed a significant surge in AI-related discourse from 2022 onward, with evolving sentiment patterns. These findings suggest a complex landscape of public AI perception, reflecting persistent concerns about societal impacts alongside increasing interest in AI’s technical aspects.

Cite this Paper

BibTeX
@InProceedings{pmlr-v295-appiah25a, title = {AI in the Public Eye: Analysing Social Media Sentiment and Opinion on Artificial Intelligence}, author = {Appiah, Ezekiel and Htait, Amal}, booktitle = {Proceedings of the UK AI Conference 2024}, pages = {1--15}, year = {2025}, editor = {Benford, Alistair and Cabrera, Christian and Kiden, Sarah and Salili-James, Arianna and Zakka, Vincent Gbouna}, volume = {295}, series = {Proceedings of Machine Learning Research}, month = {05 Aug}, publisher = {PMLR}, pdf = {https://raw.githubusercontent.com/mlresearch/v295/main/assets/appiah25a/appiah25a.pdf}, url = {https://proceedings.mlr.press/v295/appiah25a.html}, abstract = {Artificial Intelligence (AI), a rapidly evolving technology with far-reaching implications, has become a widely discussed topic on social media platforms. This study conducted a comprehensive sentiment analysis of posts discussing AI topics on Twitter, YouTube and Reddit from 2017 to 2024 to evaluate public perceptions and attitudes toward AI. A total of 133,004 social media posts were analysed using a fine-tuned RoBERTa model for sentiment classification, alongside Latent Dirichlet Allocation (LDA), n-gram, and word co-occurrence mapping for topic modelling. The analysis revealed that 46.09% of the posts express negative sentiments about AI, followed by 39.29% neutral and 14.62% positive sentiments. LDA uncovered 20 key topics, including AI ethics, job impacts, and philosophical implications. Temporal analysis revealed a significant surge in AI-related discourse from 2022 onward, with evolving sentiment patterns. These findings suggest a complex landscape of public AI perception, reflecting persistent concerns about societal impacts alongside increasing interest in AI’s technical aspects. } }
Endnote
%0 Conference Paper %T AI in the Public Eye: Analysing Social Media Sentiment and Opinion on Artificial Intelligence %A Ezekiel Appiah %A Amal Htait %B Proceedings of the UK AI Conference 2024 %C Proceedings of Machine Learning Research %D 2025 %E Alistair Benford %E Christian Cabrera %E Sarah Kiden %E Arianna Salili-James %E Vincent Gbouna Zakka %F pmlr-v295-appiah25a %I PMLR %P 1--15 %U https://proceedings.mlr.press/v295/appiah25a.html %V 295 %X Artificial Intelligence (AI), a rapidly evolving technology with far-reaching implications, has become a widely discussed topic on social media platforms. This study conducted a comprehensive sentiment analysis of posts discussing AI topics on Twitter, YouTube and Reddit from 2017 to 2024 to evaluate public perceptions and attitudes toward AI. A total of 133,004 social media posts were analysed using a fine-tuned RoBERTa model for sentiment classification, alongside Latent Dirichlet Allocation (LDA), n-gram, and word co-occurrence mapping for topic modelling. The analysis revealed that 46.09% of the posts express negative sentiments about AI, followed by 39.29% neutral and 14.62% positive sentiments. LDA uncovered 20 key topics, including AI ethics, job impacts, and philosophical implications. Temporal analysis revealed a significant surge in AI-related discourse from 2022 onward, with evolving sentiment patterns. These findings suggest a complex landscape of public AI perception, reflecting persistent concerns about societal impacts alongside increasing interest in AI’s technical aspects.
APA
Appiah, E. & Htait, A.. (2025). AI in the Public Eye: Analysing Social Media Sentiment and Opinion on Artificial Intelligence. Proceedings of the UK AI Conference 2024, in Proceedings of Machine Learning Research 295:1-15 Available from https://proceedings.mlr.press/v295/appiah25a.html.

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