This article discusses a potential social justice project using social media data. Contained in the article is a description of the social justice issue and presented in a mind map. The paper discusses the purpose of the research and why the project is exploring a potential social justice problem in social media. The analysis then speculates the ethical and privacy issues relating to the project. A final summary and status of the social justice problem conclude this paper.
The project explores social media content to find poor dietary habits in the U.S., the consumption of fast food. In the U.S. Grocery Shopper Trends 2018 report released by the Food Marketing Institute (FMI), a survey of 1,035 shoppers revealed 60% of people believed fast-food restaurants make it difficult to stay healthy (MMI Business Advisors, 2019, p. 111). The report uses gender (female/male) and generational variables (Millennial, GenX, Boomers, & Matures) (p.111). The question is, how do fast-food restaurants make it challenging to stay healthy? Enticing people with unhealthy food options can potentially be a social justice issue if fast food companies are targeting specific groups of people on social media who are more likely to eat unhealthy food. The proposed data sources come from the leading social media companies (Twitter, Instagram, Facebook, Pinterest, & Yelp), which have developer API’s available for data scientists to mine the social data available. Supplementary data sets come from the Center for Disease Control and Prevention regarding obesity in the U.S. and another data source that ranks cities with the least and most fast-food restaurants (Datafiniti, 2018). The additional data sets will help focus on the social media presence of fast-food chains.
Gillespie wrote a report discussing the “big-food” companies use tactics that don’t help society with the obesity problem, and “big-food” suggest it is the responsibility of the individual to self-regulate (Gillespie, 2019). People in 2019 should know better about the repercussions of eating fast food, and that consistent consumption leads to obesity, among other diseases. The CDC published Obesity Prevalence in 2017 and shows an alarming 35% of adults are obese in seven Midwest and southern states (CDC, 2019). Datafiniti’s report of the most and least number of fast-food chains per state surprisingly overlaps many of the U.S. States where the CDC cites obesity rates are high. The purpose of social media analysis is to see if fast-food restaurants are marketing to the people in states with high obesity. The conscious researcher should know about the obesity epidemic in the U.S., and the physiological and psychological effects fast food has on people. Are there demographics that are targeted on social media because they are known to have poor dietary habits? Is there is a link between social media advertising and areas of the U.S. that have high rates of obesity? As a social justice problem, are fast food companies contributing to the decline in American’s health and targeting areas that are already at risk of obesity?
In this project, the researcher is looking for signs of social injustice. A data researcher using social media can expose social injustice. What we do with the information is left up to interpretation. What if the researcher discovered that more impoverished people are aggressively marketed to by fast-food chains for cheap meals and discounts? What if fast food companies target specific ethnic groups, and those groups also have the highest percentage of obesity? The ethical answer would be to obtain resources and legislative authority to counter fast food marketing. Bias can also become an ethics issue in this case if the researcher was adamantly against fast food and wanted to take fast food companies to court for social injustice. Finding the first correlation in the data showing this relationship is not always the real reason behind the obesity epidemic. What happens when the research is complete, and without a doubt, fast food companies are targeting obese areas of the country? What are the implications for insurance and medical care or other related social systems that would use this information to target or ignore the exposed population?
Mining social media data will expose users’ information if they have not set the accounts to private. Care must be taken to remove personally identifiable information from the data. At this point, we want to look at the information that is not personally identifiable. The other issue is exposing a specific demographic which could be used to interpolate the identity of the people in the data study. Another easy way to breach the privacy is to mine the social data of all the people who have interacted with the fast-food restaurants in the selected media platform. Not only unethical but a breach of privacy to think one’s insurance company or medical provider is watching who is interacting with fast-food chains! Privacy is already an issue with social media; however, interpolate a demographics behavior and label the group as something else based on their interactions with fast food companies is another level of privacy breach. Social media sites that have developer API’s are part of the issue; however, without them, we wouldn’t have this rich source of social data.
The chosen project is one case of issues with social justice and yet to be determined if it is happening or not on social media. The project will take time to assimilate all of the data and look for patterns in it. The project came about with a hunch based on several published reports, and maybe there is a correlation between groups, demographics, obesity, and social media marketing that some companies have used to do unjust social actions to persuade people currently at a disadvantage health-wise, economic, or education. Social media has its other issues as Brown wrote in Is social media wrong for you? The evidence and the unknowns citing a list of the psychological problems created by social media use (Brown, 2018). Among other issues that may be related to social justice are stress, mood, anxiety, depression, sleep, addiction, self-esteem, well-being, relationships, envy, and loneliness (Brown, 2018). Are these emotional states harder for some than others, and do social justice issues single out a group more than others? Are fast food companies using Brown’s observations to their advantage? Doing more research to explore all of the questions asked in this article and ultimately working toward a better society for all persons regardless of their title.
References
Arnold, J. (December 7, 2015). 6 Ways to use social data for targeted marketing. Retrieved from: https://www.entrepreneur.com/article/253022
Brown, J. (January 5, 2018). Is social media bad for you? The evidence and unknowns. Retrieved from: http://www.bbc.com/future/story/20180104-is-social-media-bad-for-you-the-evidence-and-the-unknowns
CDC. (January 11, 2019). Adult obesity prevalence maps. Retrieved from: https://www.cdc.gov/obesity/data/prevalence-maps.html
Datafiniti. (March 16, 2018). Ranking cities with the most and least fast food restaurants. Retrieved from: https://datafiniti.co/fast-food-restaurants-america/
Gillespie, S. (January 31, 2019). The global syndemic of obesity, under nutrition, and climate change. Retrieved from: https://www.ifpri.org/blog/global-syndemic-obesity-undernutrition-and-climate-change
MMI Business Advisors. (2019). U.S. Grocery Shopper Trends 2018. p. 111. Retrieved from: http://www.mmibusinessadvisors.com/wp-content/uploads/2018/06/shopper-trends-report-2018.pdf
Sarasohn-Kahn, J. (February 5, 2019). Consumers expand their definition of well-being to include food-as-medicine. Retrieved from: https://www.healthpopuli.com/2019/02/05/consumers-expand-their-definition-of-well-being-to-include-food-as-medicine/