Website

Schedule

Mode: Virtual

Date: Sunday, July 10

8:00–9:00 Intro and Keynote
12:00–13:00 Mentorship Lunch
17:00–18:00 Panel and Goodbye

Accepted Contributions

Modeling Framing in Immigration Discourse on Social Media
Julia Mendelsohn, Ceren Budak, and David Jurgens

The framing of political issues can influence policy and public opinion. Even though the public plays a key role in creating and spreading frames, little is known about how ordinary people on social media frame political issues. By creating a new dataset of immigration-related tweets labeled for multiple framing typologies from political communication theory, we develop supervised models to detect frames. We demonstrate how users’ ideology and region impact framing choices, and how a message’s framing influences audience responses. We find that the more commonly-used issue-generic frames obscure important ideological and regional patterns that are only revealed by immigration-specific frames. Furthermore, frames oriented towards human interests, culture, and politics are associated with higher user engagement. This large-scale analysis of a complex social and linguistic phenomenon contributes to both NLP and social science research.

Affects of Remote Learning on Academic Performance of High School Students
Garima Giri, Robert M. Scott, and Snigdha Chaturvedi

The ongoing COVID-19 pandemic has resulted in prolonged school closures. Remote learning has since been a new endeavor for both students and instructors to undertake. This has resulted in personal and academic challenges for students nationwide, including increased stress levels and poorer mental health outcomes. In this project, we focus on identifying factors predictive of change in academic performance of high school students caused by the pandemic. We also predict students’ relative academic performance based on self-reported data. For collecting self-reported data, we conducted a survey to explore mental health issues and pandemic’s influence on academic achievement among high school students, aged 13 to 19 years old, in diverse neighborhoods in the mid-Atlantic region. This study’s most notable findings illustrate the correspondence between a student’s overall mental health and academic achievement during the COVID-19 pandemic. Academic institutions considering remote learning could use this research to gain a better understanding of how remote learning impacts academic performance of students and to implement resources to better support students.