9 citations · 10 across the 5 of their papers we have counts for
6 papers
Can LLMs Predict Academic Collaboration? Topology Heuristics vs. LLM-Based Link Prediction on Real Co-authorship Networks
Fan Huang, Munjung Kim
Can large language models (LLMs) predict which researchers will collaborate? We study this question through link prediction on real-world co-authorship networks from OpenAlex (9.96…
The Potential Impact of Disruptive AI Innovations on U.S. Occupations
Munjung Kim, Marios Constantinides, Sanja Šćepanović +2
The rapid rise of AI is poised to disrupt the labor market. However, AI is not a monolith; its impact depends on both the nature of the innovation and the jobs it affects. While co…
Uncovering simultaneous breakthroughs with a robust measure of disruptiveness
Munjung Kim, Sadamori Kojaku, Yong-Yeol Ahn
Progress in science and technology is punctuated by disruptive innovation and breakthroughs. Researchers have characterized these disruptions to explore the factors that spark such…
Implicit degree bias in the link prediction task
Rachith Aiyappa, Xin Wang, Munjung Kim +4
Link prediction -- a task of distinguishing actual hidden edges from random unconnected node pairs -- is one of the quintessential tasks in graph machine learning. Despite being wi…
Toxic Synergy Between Hate Speech and Fake News Exposure
Munjung Kim, Tuğrulcan Elmas, Filippo Menczer
Hate speech on social media is a pressing concern. Understanding the factors associated with hate speech may help mitigate it. Here we explore the association between hate speech a…
A Multi-Platform Collection of Social Media Posts about the 2022 U.S. Midterm Elections
Rachith Aiyappa, Matthew R. DeVerna, Manita Pote +13
Social media are utilized by millions of citizens to discuss important political issues. Politicians use these platforms to connect with the public and broadcast policy positions.…