TY - GEN
T1 - Topics, Temporal Patterns, and Network Characteristics of AI-Related Discourse on Reddit
AU - Yang, Pingjing
AU - Han, Kanyao
AU - Diesner, Jana
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.
PY - 2025
Y1 - 2025
N2 - How does the public perceive Artificial Intelligence (AI)? We present a sliver of an answer to this question by analyzing discussions on 26 AI-related subreddits from 2005 to early 2023. We apply (1) topic modeling to find latent topics that represent the gist of subreddits as collections of representative keywords, (2) network analysis to identify interaction patterns around these topics, and (3) statistics to test for correlations between AI-related topics and how they are discussed. The identified topics range from high-level AI concepts to applications and societal impacts. The temporal analysis revealed four types of topics: vanishing, resurgent, ephemeral, and emerging ones; representing the dynamic nature of public interest and concerns. We found discussions of vanishing (e.g., self-driving) and ephemeral (e.g., Metaverse) topics to lack dispersion, depth, and controversiality, while most emerging (e.g., Workplace replacement) and resurgent (e.g., Civilization and AI) topics are positively correlated with at least one of these measures. This research advances the understanding of the substance and evolution of AI-related discourse through based on Reddit data.
AB - How does the public perceive Artificial Intelligence (AI)? We present a sliver of an answer to this question by analyzing discussions on 26 AI-related subreddits from 2005 to early 2023. We apply (1) topic modeling to find latent topics that represent the gist of subreddits as collections of representative keywords, (2) network analysis to identify interaction patterns around these topics, and (3) statistics to test for correlations between AI-related topics and how they are discussed. The identified topics range from high-level AI concepts to applications and societal impacts. The temporal analysis revealed four types of topics: vanishing, resurgent, ephemeral, and emerging ones; representing the dynamic nature of public interest and concerns. We found discussions of vanishing (e.g., self-driving) and ephemeral (e.g., Metaverse) topics to lack dispersion, depth, and controversiality, while most emerging (e.g., Workplace replacement) and resurgent (e.g., Civilization and AI) topics are positively correlated with at least one of these measures. This research advances the understanding of the substance and evolution of AI-related discourse through based on Reddit data.
KW - Artificial intelligence
KW - Discussion network
KW - Fixed effects model
KW - Reddit
KW - Topic modeling
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U2 - 10.1007/978-3-031-78554-2_22
DO - 10.1007/978-3-031-78554-2_22
M3 - Conference contribution
AN - SCOPUS:85218453193
SN - 9783031785535
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 333
EP - 344
BT - Social Networks Analysis and Mining - 16th International Conference, ASONAM 2024, Proceedings
A2 - Aiello, Luca Maria
A2 - Chakraborty, Tanmoy
A2 - Gaito, Sabrina
PB - Springer
T2 - 16th International Conference on Social Networks Analysis and Mining, ASONAM 2024
Y2 - 2 September 2024 through 5 September 2024
ER -