Honors Thesis Archive
| Author | Hannah Weymouth |
|---|---|
| Title | Agricultural Social Media Content Processing utilizing the Elaboration Likelihood Model |
| Department | Communication |
| Advisor | Kelly Dillon |
| Year | 2023 |
| Honors | University Honors |
| Full Text | View Thesis (642 KB) |
| Abstract | This study aimed at determining if self-identification with a particular industry or group (in this case, the agriculture industry) affected the way messages about that industry or group were perceived, processed, and interacted upon. The Elaboration Likelihood Model (ELM) of persuasion predicts how we process and understand content which aims to be persuasive, based on a number of individual differences and situational factors. The model explains when we first see content, we process it in one of two ways: through a central or peripheral route. The peripheral route of processing required little extra consideration and time are given to the message or content versus the central route of processing requiring additional time and reflection with the message or content. In this research, focus was placed on the agriculture industry and attention was particularly paid to identification, credibility, and content and if in any instances these affected participants’ route of processing. Participants were shown messages published by either large corporate agriculture organizations like Future Farmers of America (FFA), Soil and Water Conversation Society, or National Soybean Association or those published by singular individuals such as farmers, FFA members, solar farms, and other agriculturalists or environmentalists both of which are easily for and against the agriculture industry. The first hypothesis of the study was aimed at determining if a relationship exists between individuals’ self-identification with specific industries and groups and persuasive outcomes based on the sender of messages being an individual or an organization. The data collected revealed a significant relationship between participants' likelihood to like, quote, and retweet messages that were released from organizations in comparison to messages released by individuals. The second hypothesis of the study was to determine if a relationship is present between higher self-identification with the agriculture industry and groups and persuasive outcomes based on narrative or statistical content. The data collection revealed participants were more likely to quote, like, and retweet messages containing statistics compared to messages containing narratives. Although the data revealed in the questionnaire did not allow us to directly know participants’ routes of processing, we were able to infer participants’ routes of processing based on their level identification, extent to which they found a source credible, and specific content they saw in relationship to their likelihood to engage with messages. |
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