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.
4 pages., Online via AgEconSearch, Authors explain the basic concepts of Internet+ and big data, analyze the main problems in the application of big data technology in agricultural informationization, summarize corresponding solutions from the aspects of government guidance, financial input, open sharing of agricultural big data, big data storage and processing, data mining, etc., and describe prospects ahead in the province.
Summarizes results of a non-farmer survey documenting how each of five stages of the agricultural and food business value chain is evolving in terms of data collection and use.
19 pages, via online journal, Dairy farms pose many hazards to farmers and their employees, including the risk of injury caused by handling animals. On many farms, there is a lack of consistent information and training related to farm safety topics, including stockmanship, or safe animal handling. The purpose of this qualitative research was to explore effective communication strategies that support the application of stockmanship practices and more broadly support health and safety measures and the adoption of new behaviors by farmers and their employees. Research was conducted in three stages via in-depth farm tours and in-person interviews, a qualitative survey, and follow-up phone interviews with dairy farmers. Findings identified four values and moral norms important to dairy farmers and four barriers to implementation of farm safety practices. The research also revealed publications and in-person meetings as key channels of communication and on-farm consultants as important influencers. From the research findings, three major recommendations emerged. These include using a train the trainer educational model, engaging with professionals and encouraging farmer-to-farmer communication, and leveraging digital resources.
16 pages., Via online journal., Expertise is dynamic, domain specific, and characterized according to an individual’s level of knowledge, experience, and problem-solving ability. Having expertise in the phenomenon under investigation can be used as an indicator of an individual’s aptitude to effectively serve as a coder in a content analysis or as panelist in a Delphi study. The purpose of this study was to assess 10 years of scholarship published in the premier journals of agricultural education and describe the ways researchers in agricultural communications, education, extension, and leadership disciplines who use content analysis and Delphi study methods are describing the qualifications of the people serving as expert coders and panelists. The study findings revealed the majority of researchers publishing in the premier agricultural education journals are not describing the qualifications used in selecting coders or the credentials the coders possess that would make them qualified to code the data in a content analysis. Furthermore, researchers were inconsistent citing literature that supported their selection of content analysis coders and citing literature to support a decision to describe or not to describe coders’ qualifications. However, a description of Delphi study panelists’ qualifications and citations to support why panelists were selected in a Delphi study were present in all of the Delphi studies analyzed over the 10-year period. Based on these findings, it was concluded that ACEEL researchers should include a description of coder credentials to enhance the consistency, transparency, replicability, rigor, and integrity of ACEEL research. Editors and research professionals who perform journal article reviews for the premier agricultural education journals are encouraged to note the exclusion of a description of content analysis coders’ credentials as part of the peer review process.
