Analyzing public sentiment toward GMOs via social media between 2019-2021
ABSTRACTGenetically modified organisms or GMOs offer significant advantages in food production, including increased yield, decreased pesticide usage, and better disease resistance. However, adoption and public sentiment toward GMOs is highly variable. Without positive sentiment toward GMOs, consumpt...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2023-12-01
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| Series: | GM Crops & Food |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/21645698.2023.2190294 |
| _version_ | 1797376415114461184 |
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| author | Manreet Sohi Maurice Pitesky Joseph Gendreau |
| author_facet | Manreet Sohi Maurice Pitesky Joseph Gendreau |
| author_sort | Manreet Sohi |
| collection | DOAJ |
| description | ABSTRACTGenetically modified organisms or GMOs offer significant advantages in food production, including increased yield, decreased pesticide usage, and better disease resistance. However, adoption and public sentiment toward GMOs is highly variable. Without positive sentiment toward GMOs, consumption of GMO-based foods may not have an adequate market for further investment. In order to better understand overall public sentiment toward GMO-based foods, a Boolean search was created using a commercial web-crawling service to collect and analyze public sentiment of GMOs across multiple social media and web-based services from May 1, 2019, to May 31, 2021. The Boolean query identified 2 million mentions of GMOs during the study period. Using the commercial software’s sentiment analysis (i.e. classifying mentions as either neutral, negative, or positive), 54% of the mentions were categorized as having a neutral sentiment, 32% as having a negative sentiment, and 14% as having a positive sentiment. Further emotional analysis (classifying posts by the emotion expressed, e.g., disgust, joy, sadness, anger, fear, surprise) produced by the software shows that the majority of the mentions were categorized as expressing a negative emotion: 31% of mentions expressed disgust, 28% joy, 18% sadness, 16% anger, 7% fear, and 1% surprise. Among the various social media sources collected, Twitter was the main source of data, providing 62% of the total 2 million mentions, followed by 14% from news sources and 12% from Reddit. These types of data can be used to better understand trends in sentiment toward GMOs and ultimately play an important role in combating mis-information. |
| first_indexed | 2024-03-08T19:39:24Z |
| format | Article |
| id | doaj.art-5e29216ee8b94921b2127b5a261395f6 |
| institution | Directory Open Access Journal |
| issn | 2164-5698 2164-5701 |
| language | English |
| last_indexed | 2024-03-08T19:39:24Z |
| publishDate | 2023-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | GM Crops & Food |
| spelling | doaj.art-5e29216ee8b94921b2127b5a261395f62023-12-25T13:28:19ZengTaylor & Francis GroupGM Crops & Food2164-56982164-57012023-12-011411910.1080/21645698.2023.2190294Analyzing public sentiment toward GMOs via social media between 2019-2021Manreet Sohi0Maurice Pitesky1Joseph Gendreau2Department of Computer Science, School of Letters and Science, University of California, Davis, CA, USADepartment of Population Health and Reproduction, School of Veterinary Medicine-Cooperative Extension, University of California, Davis, CA, USADepartment of Population Health and Reproduction, School of Veterinary Medicine-Cooperative Extension, University of California, Davis, CA, USAABSTRACTGenetically modified organisms or GMOs offer significant advantages in food production, including increased yield, decreased pesticide usage, and better disease resistance. However, adoption and public sentiment toward GMOs is highly variable. Without positive sentiment toward GMOs, consumption of GMO-based foods may not have an adequate market for further investment. In order to better understand overall public sentiment toward GMO-based foods, a Boolean search was created using a commercial web-crawling service to collect and analyze public sentiment of GMOs across multiple social media and web-based services from May 1, 2019, to May 31, 2021. The Boolean query identified 2 million mentions of GMOs during the study period. Using the commercial software’s sentiment analysis (i.e. classifying mentions as either neutral, negative, or positive), 54% of the mentions were categorized as having a neutral sentiment, 32% as having a negative sentiment, and 14% as having a positive sentiment. Further emotional analysis (classifying posts by the emotion expressed, e.g., disgust, joy, sadness, anger, fear, surprise) produced by the software shows that the majority of the mentions were categorized as expressing a negative emotion: 31% of mentions expressed disgust, 28% joy, 18% sadness, 16% anger, 7% fear, and 1% surprise. Among the various social media sources collected, Twitter was the main source of data, providing 62% of the total 2 million mentions, followed by 14% from news sources and 12% from Reddit. These types of data can be used to better understand trends in sentiment toward GMOs and ultimately play an important role in combating mis-information.https://www.tandfonline.com/doi/10.1080/21645698.2023.2190294Gmossentiment analysissocial mediaweb crawling |
| spellingShingle | Manreet Sohi Maurice Pitesky Joseph Gendreau Analyzing public sentiment toward GMOs via social media between 2019-2021 GM Crops & Food Gmos sentiment analysis social media web crawling |
| title | Analyzing public sentiment toward GMOs via social media between 2019-2021 |
| title_full | Analyzing public sentiment toward GMOs via social media between 2019-2021 |
| title_fullStr | Analyzing public sentiment toward GMOs via social media between 2019-2021 |
| title_full_unstemmed | Analyzing public sentiment toward GMOs via social media between 2019-2021 |
| title_short | Analyzing public sentiment toward GMOs via social media between 2019-2021 |
| title_sort | analyzing public sentiment toward gmos via social media between 2019 2021 |
| topic | Gmos sentiment analysis social media web crawling |
| url | https://www.tandfonline.com/doi/10.1080/21645698.2023.2190294 |
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