Braden, Sue (author) and Chronic Poverty Research Centre, University of Manchester, Manchester, UK
Format:
Conference paper
Publication Date:
unknown
Published:
United Kingdom
Location:
Agricultural Communications Documentation Center, Funk Library, University of Illinois Document Number: C28218
Notes:
Posted online at http://www.chronicpoverty.org/pdfs/2003conferencepapers/Braden.pdf, Presented at "Staying poor: chronic poverty and development policy," a conference at Manchester, UK from April 7-9, 2003.
21pgs, Gene-editing provides an opportunity to address the significant challenges of population growth and climate change that impact food production. Given the important role of gene-editing in our food system, exploring opportunities to persuade public acceptance of the technology is needed. The purpose of this study was to investigate persuasive effects of metaphorical concepts regarding gene-editing in agriculture. The Elaboration Likelihood Model was used as the conceptual framework. Metaphors stand to influence public acceptance because metaphors encourage issue-relevant thinking and enhance persuasion. A quantitative, randomized, between-subjects, experimental research design was delivered via an online survey to a nationally representative sample of U.S. residents. The manipulation was four mock news articles differentiated by metaphorical concept for gene-editing in agriculture (creation versus text editor versus tool versus control). Even when controlling for confounding variables, the results indicated no significant differences between the treatments on issue-relevant thinking or willingness to share the article on social media. Future research should explore the impact of metaphorical concepts on attitude and other behavioral outcomes associated with elaboration.
"Text of a paper delivered at a Workshop on Intergovernmental Planning Systems held in Champaign, Illinois March 24, 1969 under the auspices of the University of Illinois, Bureau of Community Planning." **Scott Keyes' papers held at University Archives (UIUC): Title: Scott Keyes Papers, 1920-1978 Series Number: 12/8/20.
Social Networks like Facebook, Twitter, YouTube and WhatsApp are now becoming very popular tools that are used for sharing the latest and important farming based information in different part of India. These tools are now widely used by Agricultural Extension and Advisory services to interact with the farmers for exchanging agricultural related information in India. The most influential farmers in a network can disseminate the information to the less central farmers of the network. The extension functionaries that promote the agricultural innovation will share the information with the most central members which in turn will share it with maximum number of the members of a social network. Social Network Analysis (SNA) acts as an efficient analytical tool that helps us to understand the relationship between farmer stakeholders and the importance of a farmer's position in the entire network. In this paper, a structural analysis of the Social Network is performed over two datasets, namely, Facebook-like dataset and Twitter Lists dataset. Here, we have studied the importance of individual nodes in the network through various centrality measures. SNA properties like centralities are used to represent the most central nodes that can act as a good influence spreader in the network. In this paper, initially the k-core decomposition method is used to find a set of influential nodes among all the nodes in the network. It is done to reduce the computational time. Our simulation shows that the nodes with higher Page Rank centrality can activate more members in a network as compared to other centrality measures. For Information diffusion, we have used Linear Threshold (LT) Model to understand the influence spread of the central farmers in the network.
