19 pages., via online journal article, Best management practices (BMPs) are suggested practices that help agricultural producers optimize production while reducing pollution, soil erosion, and other environmental impacts. Many audiences, including scientists and policy makers, have expressed disappointment at the current level of BMP use. Elaboration likelihood model (ELM) is used to understand how people process messages. ELM states that people can process messages either centrally or peripherally. This study sought to understand how producers processed information related to BMP adoption in grazing systems. Researchers conducted qualitative, in-depth interviews with 42 beef-cattle producers in Kansas and Oklahoma. It was found producers process information both centrally and peripherally, more specifically through past experiences and visual observations. This study suggests that when promoting BMPs, communicators should use visual cues to help producers process information. More importantly communicators should utilize strategies that encourage producers to reflect on past experiences to promote central processing.
22 pages., via online journal., Scientists are frequently asked to broadly share their expertise and research with a variety of audiences, beyond typical academic circles in their home disciplines. That could include developing community engagement programs, school outreach, leveraging online social networks, and other activities. The purpose of this study was to examine U.S. agricultural and natural resources (ANR) scientists’ typical science communication channels, their experiences utilizing Twitter for sharing their knowledge, research, and engaging in online public science discussion. Diffusion of Innovations theory and the model of science in-reach versus outreach guided this study. Researchers used a qualitative case study design. Data collection included ANR scientist interviews (n = 8) and application of Internet-based research methods for observing scientists’ Twitter activities. Four themes emerged from the data: 1) academic journals and conferences as scientists’ typical communication channels, yet Extension efforts help to broaden audiences, 2) scientists expected research to be peer-reviewed before public dissemination to combat misinformation and spreading of ‘junk science’, 3) scientists balanced professionalism, personalization, promotion, and Twitter hashtags for engagement, and 4) scientist-identified barriers to using Twitter included lack of time and avoiding heated discussions. Recommendations include revisiting scientists’ job descriptions and expectations for online science engagement. Also, there should be continual development and implementation of science communication training for scientists targeting best Twitter practices, growing followers for outreach beyond academic colleagues and groups, using visuals for online engagement, intentional scheduling for social media, and how to effectively navigate heated online discussions.
Garrett M. Steede (author), Courtney Meyers (author), Nan Li (author), Erica Irlbeck (author), Sherice Gearhart (author), and Texas Tech University; University of Minnesota - Twin Cities
Format:
Journal article
Publication Date:
2018
Published:
USA
Location:
Agricultural Communications Documentation Center, Funk Library, University of Illinois Box: 149 Document Number: D10103
Article 4; pgs. 1-16, On January 1, 2017, the final rule of the Veterinary Feed Directive (VFD) was put into place requiring
antibiotics approved for both humans and animals to be discontinued for growth promotion. This change was
brought on by the role growth promoters in livestock production play in the development of antibiotic
resistance. Antibiotic resistance increases the costs associated with human health care by increasing the length
of stays in the hospital and requiring more intensive medical care for patients. The purpose of this study was to
explore sentiment and characteristics of social media content and the characteristics of the key influencers
whose opinions had the greatest amount of reach on social media in regard to antibiotic use in livestock and
antibiotic resistance. Nuvi, a social media monitoring program, provided sentiment for each tweet and coded
64.8% of the content (n = 129) as negative compared to 38.2% (n = 76) humans coded as negative. The
contrast between human coders and Nuvi indicates there could be discrepancies between how Nuvi codes
content and the way a human might interpret the content. No key influencer discussed antibiotic use in
livestock positively. Findings suggest agricultural communicators should not rely completely on the output
from sentiment analysis programs to evaluate how the public discusses issues related to agriculture,
particularly controversial issues. Further, agricultural communications practitioners should prioritize
monitoring the content shared by key influencers in an effort to better understand the content being shared by
the most influential users. Recommendations for future research are provided.
