Data For Good: The Consequences of Language Policing
Contestation over language use is an unavoidable feature of American politics. Yet, despite the rise of language policing on both sides of the aisle, we know surprisingly little about how ordinary citizens respond to norms governing language use from both in-group and out-group members. Following Munger (2017), I would like to leverage social media platforms such as Reddit and Twitter to evaluate whether injunctions to use particular words (e.g., undocumented immigrant, Latinx) are effective. I plan to use an experimental approach, where conditional on mentions of “illegal alien” or “Hispanic/Latino,” users are randomly assigned to receive a “language correction.” Outcome measures would include subsequent use of corrected terms, valence of user responses, and upvoting/liking/RTing behavior.
The Data For Good program is designed primarily for volunteers, however one candidate will be selected as a project coordinator and will receive a stipend via the Data For Good Scholars program. In addition to the responsibilities of a team member, the selected candidate will be responsible for keeping up-to-date notes on the project’s status, writing an end-of-period report, and attending bi-weekly meetings with a DFG program director. The project coordinator should strive to keep the group of volunteers in sync with the needs of the project owner.
Project Owner
- Professor: Yamil Ricardo Velez
- Department/School: Department of Political Science
- Location: IAB 741
- My research explores how people perceive their communities, and how those experiences within those communities affect the way they think about politics.
Project Timeline
- Earliest starting date: 3/1/2020
- End date: 5/31/2020
- Number of hours per week of research expected during Spring 2020: ~8
Candidate requirements
- Skill sets: Text analysis; web scraping; experimental methods
- Student eligibility:
freshman,sophomore, junior, senior, master’s - International students on F1 or J1 visa: eligible