A text analytics model for agricultural knowledge discovery and sustainable food production: A case study from Oklahoma Panhandle

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dc.contributor.authorBagheri, A.
dc.contributor.authorTaghvaeian, S.
dc.contributor.authorDelen, D.
dc.date.accessioned2024-05-19T14:33:17Z
dc.date.available2024-05-19T14:33:17Z
dc.date.issued2023
dc.departmentİstinye Üniversitesien_US
dc.description.abstractWith recent increases in the use of social media in agricultural communities, many farmers are showing more and more interest in participating in social media and sharing different aspects of their profession with peers and policymakers. However, researchers have not explored this valuable data source well enough to help improve agribusiness decision-making. This study aims to investigate the potential capability and richness of social media for agricultural knowledge discovery, which can help monitor, detect, and predict critical agricultural events and activities and develop more sustainable food production and agricultural economy. This research utilizes text-mining tools and techniques to collect, process, and mine unstructured textual data from Twitter. Then, it examines the agreement between the retrieved information from tweets and that from the current monitoring systems and common cultural practices. Our findings illustrate that social media data can effectively provide information regarding the commencement and duration of significant cultural activities This study also examines the classification performance of several popular sentiment analysis tools on the farmer's tweets and provides suggestions for future research on domain-specific sentiment lexicons for agricultural purposes. © 2023 The Author(s)en_US
dc.identifier.doi10.1016/j.dajour.2023.100350
dc.identifier.issn2772-6622
dc.identifier.scopus2-s2.0-85182161228en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.urihttps://doi.org/10.1016/j.dajour.2023.100350
dc.identifier.urihttps://hdl.handle.net/20.500.12713/4175
dc.identifier.volume9en_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherElsevier Inc.en_US
dc.relation.ispartofDecision Analytics Journalen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.snmz20240519_kaen_US
dc.subjectAgricultureen_US
dc.subjectKnowledge Discoveryen_US
dc.subjectSentiment Analysisen_US
dc.subjectSocial Media Analyticsen_US
dc.subjectSustainable Food Productionen_US
dc.subjectText Analysisen_US
dc.titleA text analytics model for agricultural knowledge discovery and sustainable food production: A case study from Oklahoma Panhandleen_US
dc.typeArticleen_US

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