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20222026
most citedCan we trust the evaluation on ChatGPT?

66 citations · 108 across the 11 of their papers we have counts for

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6 papers · 1 filter

cs.SI2026

Emergence of Stereotypes and Affective Polarization from Belief Network Dynamics

Ozgur Can Seckin, Rachith Aiyappa, Madalina Vlasceanu +3

Our belief systems are shaped by social processes, such as observations and influence, and by cognitive processes, such as the drive for internal coherence. These processes steer h…

cs.SI2024★ 1 cited

How the cascade inference problem distorts information diffusion

Matthew R. DeVerna, Francesco Pierri, Rachith Aiyappa +3

To analyze the flow of information online, experts often rely on platform-provided data from social media companies, which typically attribute all resharing actions to an original…

cs.SI2024★ 1 cited

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…

cs.SI2023★ 9 cited

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.…

cs.SI2023★ 13 cited

Emergence of simple and complex contagion dynamics from weighted belief networks

Rachith Aiyappa, Alessandro Flammini, Yong-Yeol Ahn

Social contagion is a ubiquitous and fundamental process that drives individual and social changes. Although social contagion arises as a result of cognitive processes and biases,…

cs.SI2022★ 13 cited

Identifying and characterizing superspreaders of low-credibility content on Twitter

Matthew R. DeVerna, Rachith Aiyappa, Diogo Pacheco +2

The world's digital information ecosystem continues to struggle with the spread of misinformation. Prior work has suggested that users who consistently disseminate a disproportiona…