Location
Hilton Hawaiian Village, Honolulu, Hawaii
Event Website
https://hicss.hawaii.edu/
Start Date
3-1-2024 12:00 AM
End Date
6-1-2024 12:00 AM
Description
Chatbots, such as ChatGPT, are a rapidly emerging technology because of their potential applications in many fields. Existing research has addressed chatbot user adoption, mostly through experimental studies. Despite the increasing relevance of applying big data analytics to social media data to ascertain user impressions, research from this perspective on chatbot adoption is scarce. Therefore, this exploratory research investigates the topics of 44,310 conversations from the platform Reddit by applying deep learning topic modeling, sentiment analysis, and question-answering retrieval modeling combined with qualitative content analysis. This study (1) examines the topics associated with chatbots regarding the adoption process over the last seven years, (2) draws on the Unified Theory of Acceptance and Use of Technology 2 to refine the key chatbot user adoption factors, and (3) is an early contribution of applying deep learning textual analysis in this context.
Recommended Citation
Pawlik, V. Phoebe and Pan, Yan, "Inferences from Social Media Conversations about the Adoption of Chatbots" (2024). Hawaii International Conference on System Sciences 2024 (HICSS-57). 10.
https://aisel.aisnet.org/hicss-57/dsm/data_analytics/10
Inferences from Social Media Conversations about the Adoption of Chatbots
Hilton Hawaiian Village, Honolulu, Hawaii
Chatbots, such as ChatGPT, are a rapidly emerging technology because of their potential applications in many fields. Existing research has addressed chatbot user adoption, mostly through experimental studies. Despite the increasing relevance of applying big data analytics to social media data to ascertain user impressions, research from this perspective on chatbot adoption is scarce. Therefore, this exploratory research investigates the topics of 44,310 conversations from the platform Reddit by applying deep learning topic modeling, sentiment analysis, and question-answering retrieval modeling combined with qualitative content analysis. This study (1) examines the topics associated with chatbots regarding the adoption process over the last seven years, (2) draws on the Unified Theory of Acceptance and Use of Technology 2 to refine the key chatbot user adoption factors, and (3) is an early contribution of applying deep learning textual analysis in this context.
https://aisel.aisnet.org/hicss-57/dsm/data_analytics/10