Spring 2023
Cross-platform influencers research group
Note this DRG is at capacity and no longer accepting applications.
We are looking to recruit 3-4 students to participate in a Directed Research Group led by Center for an Informed Public PhD students Kristen Engel and Morgan Wack, and advised by Professors Kate Starbird (HCDE) and Emma Spiro (iSchool).
This project will examine how misinformation about elections spreads across social media platforms. Specifically, we will focus on the accounts of individual users that spread large quantities of false and misleading information during the 2020 and 2022 elections to study how their posts differ depending on the social media platform they are using. Students will work with CIP researchers to manually identify and categorize social media posts and comments via qualitative coding methods.
Students would enroll in HCDE 496 (for undergraduates) and HCDE 596 (for graduate students) for 2 credits during the spring quarter and be expected to spend 6 hours per week on the project. Interested students should complete the application form below. Selected students will be given an add code for the course. You can find a description of the study aims and desired student qualifications below.
Project description (2 credits/6 hours per week)
Despite growing user-bases and influence in American politics, limited data currently exists regarding the spread of misinformation outside of mainstream platforms. This project will enable look to fill this gap by collecting and comparing the actions of “repeat spreaders” of misinformation across four text-based social media platforms: Truth Social, Parler, Gettr, and Twitter. To generate novel insights on both differences in the actions of these repeat spreaders and their interaction with distinct platform users, this project will leverage new data from repeat spreaders of misinformation on Twitter linked to the 2020 and 2022 U.S. Elections. Using this data, we will collectively be able to answer several interesting questions, including:
- How does the content and subject matter of prominent spreaders of misinformation differ by platform?
- How does engagement with misinformation-linked posts differ based on the platform policies and user bases?
- Do different strategies implemented by prominent spreaders predict the virality of misinformation across platforms?
- How do users on non-mainstream platforms engage with misinformation compared to mainstream social media?
Qualifications: Students with prior qualitative coding experience, experience developing qualitative coding schemas, and a general understanding of online misinformation, U.S. politics, or non-mainstream social media platforms will be strong candidates for this project.
Note this DRG is at capacity and no longer accepting applications.
Spring 2023
Negative Affect Research Group
Led by HCDE PhD Candidate Andrew Beers and Associate Professor Kate Starbird
Note this DRG is at capacity and no longer accepting applications.
Social media metrics privilege “positive” affect. Famously, Facebook, Twitter, TikTok, and other platforms do not have “dislike” buttons, and consequently many social media datasets available to researchers are concerned with positivity: likes, shares, follows, endorsements, etc. And yet public debate often centers around social media’s potential for negative affect. Many are concerned about the extent and severity of targeted social media harassment, which terrorizes individuals and can mute the online expression of entire communities. Group expressions of disgust, contempt, or ridicule seem to typify everyday interaction on social media platforms, causing a moral panic around “cancel culture” for some and a discourse around the beneficial effects of shaming and consequences for others. Some platform users seem to intentionally cultivate negative affect, transforming their controversial statements into social capital via the influencer economy. Even the utopian dream, rarely reached, of the internet as a forum for productive debate presupposes that disagreement would be a common feature of its everyday usage.
This research group seeks to understand how negative affect is expressed on popular social media platforms, what the consequences of those expressions are, and popular debates on the prospect for designing for (or against) negative affect. Half of our time will be committed to reading and discussing published research which investigates negative affect on social media from a variety of methods and perspectives. The other half will be committed to annotating a large dataset of quote tweet interactions on Twitter between popular United States political accounts, including politicians, journalists, activists, influencers, and media outlets. By annotating quote tweet interactions, frequently noted for their negative affect, we aim to both A) develop a repeatable codebook for and a deeper understanding of negativity online and B) generate a seed dataset which can be used to automatically classify future data and better understand the qualities of negativity at scale.
Note this DRG is at capacity and no longer accepting applications.
Spring 2023
Understanding TikTok User Behavioral Changes After Sudden Bursts of Increased Attention
Led by HCDE PhD Student Joey Schafer with guidance from Professor Kate Starbird
Note this DRG is at capacity and no longer accepting applications.
Current social media platforms like TikTok facilitate sudden convergence on particular users or videos, giving them a much larger audience than they were previously accustomed to. This sudden increase in attention can be quite disorienting for users, who are suddenly thrust into a much more visible, public online space. In this DRG, we will be interviewing U.S. TikTok users who have experienced what they self-identified as viral events, in order to understand what this experience was like and the impacts that this had on their use of social media platforms.
We are looking for 2-4 students who have experience with social media (especially TikTok), interviewing, and visual data analysis for this 2-credit DRG. Students from all academic levels are invited to apply and participate in this project. DRG students will meet for approximately 1 hour weekly and are expected to contribute an additional approximately 5 hours per week, such as through background readings, participant scheduling and interviews, transcribing interview recordings, and memoing on themes found in interviews. Group meetings will occur on either Monday or Wednesday afternoons depending on student schedules. Note this DRG is at capacity and no longer accepting applications.
Winter - Spring 2023
Examining the Spread of Election Rumors Online
Led by Sukrit Venkatagiri (Postdoctoral Scholar), Emma Spiro (iSchool), and Kate Starbird (HCDE)
Note this DRG is at capacity and no longer accepting applications.
The 2022 midterm elections were the focus of a wide range of rumors and conspiracy theories. In Autumn, in a first stage of research, our team at the Center for an Informed Public identified hundreds of different claims about the election that were false, misleading, and/or unsubstantiated. Now, in a second stage, our team aims to classify these different claims, identify social media posts from a variety of platforms related to these claims, and analyze social media content around these claims to answer a variety of research questions about how rumors spread online during the 2022 election period.
We are looking for students with a range of different skills. First and foremost, all students must have familiarity with social media, an interest in the processes and procedures around elections, and a willingness to engage in qualitative analysis of social media posts. We are also looking for students who, in addition to those interests/skills, have experience with data science (writing code to analyze data), network science, visualization, and statistical/machine learning. We encourage students with journalism and political science backgrounds to apply as well.
Note this DRG is at capacity and no longer accepting applications.