The paper makes a distinction between GMO discussions by laypeople and organizational entities on Twitter. Using text classifiers, topic modeling, and sentiment analysis, it addresses questions about popular topics, changes over time, and sentiments regarding GMO-related tweets.
Title
Understanding Perceptions and Attitudes toward Genetically Modified Organisms on Twitter
Summary
َAuthor
Inyoung Jun, Yunpeng Zhao, Xing He, Rania Gollakner, Christa Court, Olga Munoz, Jiang Bian, Ilaria Capua, Mattia Prosperi
Year
2020
َThematic Area
Agri-Food
Topic
GMO & Misinformation
Country
Canada
Region
North America
Misinformation Combatting
Misinformation Source
Place Published
APA 7th End Text Citation
Jun, I., Zhao, Y., He, X., Gollakner, R., Court, C., Munoz, O., Bian, J., Capua, I., & Prosperi, M. (2020). Understanding Perceptions and Attitudes toward Genetically Modified Organisms on Twitter. International Conference on Social Media and Society, 291–298. https://doi.org/10.1145/3400806.3400839