CDS Directed Research Projects - Spring 2020
In the Spring of 2020 students from the Critical Data Studies - Data Mine Learning Community were encouraged to participate in a directed research experience with faculty from African American Studies, the Department of Anthropology, the Honors College and the Libraries and School of Information Studies. Students were embedded in faculty-led research teams and were asked to bring their individual skill sets, experience and knowledge gained via independent Fall CDS projects and theoretical discussions (HONR 399 and ILS 595) to each team. Directed research students were asked to submit a poster based on the research experience to the 2020 Spring Purdue Office of Undergraduate Research Conference. Below are the CDS-Data Mine student abstracts which were accepted and presented at the Spring 2020 OUR Conference poster sessions. We are working with the students and research faculty to make the posters available in the near future.
Carter Bruns, Jack Harber, Sarahy Duenas, Vishnu Kamagere, David Nickel* and Alexander Patton.*
"Good Decisions, Good Data." Research Mentor: Jason Ware, Honors College. (*non-CDS cohort collaborators)
Abstract: Through partnering with the City of Lafayette, we generated primary research data and analyzed secondary data sources to focus on Lafayette’s transportation methods, neighborhood revitalization, and affordable housing outcomes. In researching modes of transportation, we found that City of Lafayette residents mainly drive alone, car-pool, and/or use public transportation. Workers 16-and-over in owner-occupied housing units were primarily found to carpool while workers 16-and-over in renter-occupied housing units were primarily found to use public transportation. In analyzing neighborhood revitalization, we conducted phone interviews and online surveys with Lafayette residents that participated in the Habitat for Humanity home building process. We found that citizens’ quality of life and happiness levels improved after having their new home built. Additionally, we studied the possible effect of race, age, and gender on poverty/homlessness rates. Initial data gathered suggests there may also be a correlation between the shift of populations in these neighborhoods and the poverty rate. Lastly, for affordable housing, we examined demographic and financial trends of Northend Lafayette mortgage purchasers. In many Northend neighborhoods, the median income of mortgage applicants has consistently hovered around 50% of the Greater Lafayette area’s median income. The value of the mortgages also has greatly concentrated toward $70k over time, with more FHA-Insured loans originating in 2018 than previously. These trends show a stable and affordable environmentwithin the Northend housing market, but also show that the city may need to put greater emphasis on neighborhood revitalization to increase the overall attractiveness of living in these areas.
James Darschewski and Nathan Garrison.
"#YouTubeBlack and the Politics of Platform and Promotion." Research Mentor: Dr. Faithe Day, Purdue Library and School of Information Studies
Abstract: Discrimination of Black content creators on YouTube has become evident in recent years as more and more viewers and creators utilize the platform. In2016, Google created the event #YouTubeBlack as a response to this discrimination within and outside of the platform. Despite the initial purpose of #YouTubeBlack, over the years it has become a pseudo-event which focuses on promoting token Black content creators instead of building up the aspiring Black YouTubers who want to be included in the #YouTubeBlack movement. Using Grounded Theory and the method of Open Coding, we compiled 100 YouTube videos using hashtag #YouTubeBlack as a search protocol, we categorized the video content using the metadata of views, likes, dislikes, number of subscribers, comments, and additional video content data. Based on this data collection and categorization, we discovered that certain videos were more popular and frequently recommended than other videos within the platform. Using this initial observation, we developed research topics and questions that would spearhead our investigation into the #YouTubeBlack movement. The research questions are as follows: “What are the norms of recommendation and promotion on YouTube?”, “What is the logic behind the popularity of specific #YouTubeBlack Videos?”, and “What are the strategies that content creators are using to increase their visibility within the platform?”. This research project should encourage future change in the YouTube platform and bring awareness to the discriminatory design that indirectly privileges certain creators and content while actively suppressing others.
Matthew Der.
"Analyzing Participant Motivation at Hackathons and Its Effects on Future Participation." Research Mentor: Bethany McGowan, Purdue Libraries and School of Information Studies
Abstract: Hackathons are events where participants work to design and create solutions aimed towards a particular theme or issue, often reflecting the state of the real world. Recently, hackathons have gained popularity due to their innovative nature and collaborative environment. This research project will explore the theme of maintaining participants’ motivations throughout the extent of a hackathon by analyzing the following questions: What initially motivates competitors to participate in hackathons?; What trends, if any, exist amongst participants who compete in the entire hackathon?; If trends emerge, what role might they play in determining the likelihood of the competitor attending future hackathons? We conducted a literature review, interviewed hackathon participants, then analyzed the interview responses to determine that a main reason why participants join hackathons is their interest in certain fields and the opportunity to learn more. Furthermore, participants are more likely to compete in future hackathons when they are collaborative and group-based, rather than working individually.
Calvin Du.
"Hackthons: Motivation and Mantaining Members." Research Mentor: Bethany McGowan, Libraries and School of Information Studies.
Abstract: Hackathons are interdisciplinary, competitive, and theme-oriented events where participants aim to find efficient solutions through an educational experience. Completed both individually and collectively, they are becoming increasingly popular, gaining traction for their advocacy of problem-solving techniques and innovation. This project will analyze the following two questions: What are the participants’ motivation for joining hackathons? And what methods can weemploy to improve participant retention? In order to answer these, we used a four-step process. First, student preliminary survey data consisting of skills level, year, and major were collected and analyzed. Then, as each week of the hackathon passed, dropouts were interviewed to understand their motives, as well as to find possible improvements to the overall process. Finally, literature reviews were conducted and participants’ response patterns were analyzed. This helped us create written and visual models, which illustrate initial motivation, participant information, and successful hackathon layouts. Ultimately, we discovered that a main reason participants join hackathons is to learn data analyzing skills to apply to their respective majors; and in order to maintain their motivation and interest throughout the entire process, two main characteristics must be well-executed: a well-organized planning phase as well as an effective and friendly mentor-hacker relationship.
Nikita Gerard and Antonio Dominguez Palomar.
"A Critical Data Studies Analysis of Smart Campus Recruitment Technology." Research Mentor: Lindsay Weinberg, Innovative Studies.
Abstract: The purpose of this study is to analyze the history of existing student data regulations in order to observe their relevance and applicability to current data collection technologies and predictive analytics models used by universities to recruit prospective students. Drawing from the discipline of critical data studies, we utilize frameworks involving critical platform studies, data colonialism, and surveillance studies to understand how universities’ definition of “successful” targeting and recruitment using predictive modeling can limit equitable opportunities for students, particularly those belonging to marginalized groups. We employ a discourse analysis on present policies regulating student data privacy, as well as industry and academic literature describing the predictive analytics used for universities’ recruitment strategies, in order to investigate how private corporations and highereducation institutions frame the utility of these technologies. Additionally, we study cases of student data protection initiatives from universities in the U.S. and U.K. to critically analyze their impacts on students and institutions. Based on this interdisciplinary analysis, we make recommendations for how student data regulations can be more responsive to recruitment technologies, placing emphasis on algorithmic transparency as a means of facilitating the identification and mitigation of systematic bias within such technologies.