The following findings were derived from the experimental design outlined in a previous post, entitled “A dataset of my very own,” in which participants answered survey questions and uploaded screenshots of posts from their own Facebook newsfeeds.
The summer session is coming to a close, and while that does not mean an end to my work, it does mean that I have to leave William & Mary until the start of the fall semester. Some of the data I am working with for the lab can only be accessed with software on computers here on campus, so I am making a strong push to finish with that project in the next two days.
Data collection is complete! This project has been in development in one form or another for months, and the full analysis will occupy me for some time to come, but the study itself took just a few hours. After going through several iterations, the final research design was an online survey, albeit a slightly unconventional one. Respondents each uploaded three screenshots of posts from their Facebook newsfeeds, either posts about politics (the treatment group) or about sports (the control group). Afterwards, they responded to a series of survey items about their political opinions. Once this research design was decided upon, the project moved very quickly, from building and testing the survey on Qualtrics to releasing it on Amazon Mechanical Turk. Perhaps the most stunning was the revelation that a survey I launched in the early evening had met its response quota before the end of night. Now, after all the planning and preparation, I have an actual dataset of my own to analyze, plus a folder full of Facebook screenshots in need of coding! While the results may support or fail to provide evidence for the hypotheses, it is incredibly gratifying to finally be able to engage with the theory beyond just my own speculation. Regardless of what the analysis shows, I am truly grateful to have had the opportunity to make this project a reality.
I am currently searching the existing literature about Facebook use in order to find studies that use experimental designs in which the participants interact with their own social media accounts. So far, this search has been both uniquely challenging and rewarding. When conducting literature reviews in the past, I always focused on the theory and findings presented in various articles. Thus, the introduction, results, and discussion sections drew my attention more than anything else. Now the tables have turned, and I am searching methods sections for a type of experiment, no matter the theory behind it. Unfortunately, article titles and keywords tend not to focus on the methods, hence my challenge. However, this search has forced me to engage with bodies of social psychology literature I had never thought to explore. I now know more than I ever expected to about narcissism, envy, loneliness, and a variety of other topics. This search, challenging as it is, has become a chance to expand my horizons, and a reminder that there is a plethora of engaging research taking place outside of my political psychology niche.
This project will be conducted through the Social Networks and Political Psychology (SNaPP) Lab, directed by Professor Jaime Settle. Its purpose is to determine the effects of exposure to political content on Facebook on Facebook users’ political attitudes, including political ideology and candidate preferences. Despite extensive research on the relationship between social media and politics, there has yet to be a direct investigation into whether or not political posts on Facebook affect the beliefs of those viewing them. A significant portion of the research will be devoted to developing a method for realistically testing this relationship using actual content from participants’ own Facebook timelines. An examination of the methodologies of existing social media studies (both inside and outside of political science) will help to determine the best approach for this study. The time this summer will be used to design and pilot test research ideas with the goal of creating a research design that can be conducted in the fall of 2016 as part of the Omnibus project.