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.
14 pages, via online journal, Designing effective policies for economic development often entails categorizing populations by their rural or urban status. Yet there exists no universal definition of what constitutes an “urban” area, and countries alternately apply criteria related to settlement size, population density, or economic advancement. In this study, we explore the implications of applying different urban definitions, focusing on Tanzania for illustrative purposes. Toward this end, we refer to nationally representative household survey data from Tanzania, collected in 2008 and 2014, and categorize households as urban or rural using seven distinct definitions. These are based on official administrative categorizations, population densities, daytime and nighttime satellite imagery, local economic characteristics, and subjective assessments of Google Earth images. These definitions are then applied in some common analyses of demographic and economic change. We find that these urban definitions produce different levels of urbanization. Thus, Tanzania's urban population share based on administrative designations was 28% in 2014, though this varies from 12% to 39% with alternative urban definitions. Some indicators of economic development, such as the level of rural poverty or the rate of rural electrification, also shift markedly when measured with different urban definitions. The periodic (official) recategorization of places as rural or urban, as occurs with the decennial census, results in a slower rate of rural poverty decline than would be measured with time-constant boundaries delimiting rural Tanzania. Because the outcomes of analysis are sensitive to the urban definitions used, policy makers should give attention to the definitions that underpin any statistics used in their decision making.
