User acceptance on content optimization algorithms: predicting filter bubbles in conversational AI services
Crossref DOI link: https://doi.org/10.1007/s10209-022-00913-8
Published Online: 2022-09-05
Published Print: 2023-11
Update policy: https://doi.org/10.1007/springer_crossmark_policy
Cho, Hosoo
Lee, Daeho
Lee, Jae-Gil https://orcid.org/0000-0001-7376-4480
Funding for this research was provided by:
Ministry of Education (NRF-2021S1A5B5A16077452)
Text and Data Mining valid from 2022-09-05
Version of Record valid from 2022-09-05
Article History
Accepted: 26 August 2022
First Online: 5 September 2022
Declarations
:
: The authors declare that they have no conflict of interest.