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AuthorYadav, Jitendra
AuthorYadav, Avikshit
AuthorMisra, Madhvendra
AuthorZhou, Jianlong
AuthorRana, Nripendra P.
Available date2024-07-25T10:18:18Z
Publication Date2023-07-17
Publication NameCommunications of the Association for Information Systems
Identifierhttp://dx.doi.org/10.17705/1CAIS.05240
CitationYadav, J., Yadav, A., Misra, M., Rana, N. P., & Zhou, J. (2023). Role of social media in technology adoption for sustainable agriculture practices: Evidence from Twitter analytics. Communications of the Association for Information Systems, 52(1), 833-851.
ISSN1529-3181
URIhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85163717738&origin=inward
URIhttp://hdl.handle.net/10576/57126
AbstractSocial networking sites provide a new means of communication for disseminating cutting-edge agricultural technologies. These are unmediated interaction channels that enable a user to communicate their experience with technology and generate negative or positive attitudes that impact technology adoption decisions. We employ a machine learning approach to analyse users' existing semantic predisposition for technology adoption in agriculture at various operational levels. While developing attitudes toward technology adoption, these semantic tendencies become an important aspect of users' cognitive decision making. The study scrapes user comments and conversations about agritech on Twitter through data mining. The research also explains the important characteristics that enhance attitude building on Twitter and are responsible for reinforcing decision making among information seekers using four machine learning models. Based on the results, the research recommends strategies to managers for better communication with agriculturists and enhancement of users' decision making.
Languageen
PublisherAssociation for Information Systems (AIS)
SubjectAgriculture Technology
Attitude Formation
Machine Learning
Predictive Modelling
Social Media
Technology Adoption
TitleRole of Social Media in Technology Adoption for Sustainable Agriculture Practices: Evidence from Twitter Analytics
TypeArticle
Pagination833-851
Volume Number52
dc.accessType Full Text


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