Semantic Network Analysis Reveals Opposing Online Representations of the Search Term “GMO”

• Published in: Global challenges Vol. 2; no. 1; pp. 1700082 - n/a
• Main Authors: Jiang, Ke, Anderton, Brittany N., Ronald, Pamela C., Barnett, George A.
• Format: Journal Article
• Language: English
• Published: Germany John Wiley & Sons, Inc 22.01.2018; John Wiley and Sons Inc; Wiley
• Subjects: Agriculture; concept co‐occurrence; Content analysis; Crops; Decision making; Environmental impact; Food; Food sources; Genetic engineering; Genetic modification; genetically engineered foods; Genetically engineered organisms; Genetically modified organisms; GMO; Influence; Internet; Network analysis; online information; Public opinion; Public policy; Search engines; semantic network analysis; Semantics; Sentiment analysis; Software; Web sites; Websites; United States > US; online information; GMO; genetically engineered foods; concept co‐occurrence; semantic network analysis
• ISSN: 2056-6646; 2056-6646
• DOI: 10.1002/gch2.201700082

Making sound food and agriculture decisions is important for global society and the environment. Experts tend to view crop genetic engineering, a technology that can improve yields and minimize impacts on the environment, more favorably than the public. Because there is a causal relationship between public opinion and public policy, it is important to understand how opinions about genetically engineered (GE) crops are influenced. The public increasingly seeks science information on the Internet. Here, semantic network analysis is performed to characterize the presentation of the term “GMO (genetically modified organism),” a proxy for food developed from GE crops, on the web. Texts from three sources are analyzed: U.S. federal websites, top pages from a Google search, and online news titles. We found that the framing and sentiment (positive, neutral, or negative attitudes) of “GMO” varies across these sources. It is described how differences in the portrayal of GE food by each source might affect public opinion. A current understanding of the types of information individuals may encounter online can provide insight into public opinion toward GE food. In turn, this knowledge can guide teaching and communication efforts by the scientific community to promote informed decision‐making about agricultural biotechnologies. Web results : A computational approach known as semantic network analysis is used to create visual representations of the way in which “GMO (genetically modified organism),” a proxy for genetically engineered (GE) food, is represented in distinct areas of the Internet. This study empirically shows that the presentation of GE food differs dramatically between sources, including Google search, news titles, and federal webpages.