We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
A sentiment analysis model of agritech startup on Facebook comments using naive Bayes classifier.
- Authors
Kewsuwun, Nawapon; Kajornkasirat, Siriwan
- Abstract
Facebook page is a tool able to generate perceptions and acceptance, and support people and investors in making business decisions. Moreover, Facebook page plays a part in engaging people in the form of a community. People share experiences and opinions toward products, services, and trends in particular periods on the Facebook page community. Regarding sentiment analysis on Facebook pages, most education and other general topics in English have only been analyzed in English. However, sentiment analysis regarding agritech startups topics in Thai language has not been done yet. This study analyzes opinions and categorizes positive and negative comments by using naive Bayes classifier to examine the sentiments and attitudes of people and investors. The results could possibly reflect the perception rate of agritech startups in Thailand and could be applied to explain attentiveness and assess people's engagement opinions. Furthermore, it could be applied in studying consumer behavior, marketing analysis, spread of information, and attitudes. The study's model is generic and could be applied in other contexts to provide insightful suggestions.
- Subjects
THAILAND; NAIVE Bayes classification; SENTIMENT analysis; AGRICULTURAL technology; CONSUMER behavior; COMMUNITIES
- Publication
International Journal of Electrical & Computer Engineering (2088-8708), 2022, Vol 12, Issue 3, p2829
- ISSN
2088-8708
- Publication type
Academic Journal
- DOI
10.11591/ijece.v12i3.pp2829-2838