66 citations · 108 across the 11 of their papers we have counts for
11 papers
IntentTune: Using user demand and personalization to resolve "unknown" query intents for e-commerce search
Rachith Aiyappa, Ishita Khan, Chester Palen-Michel +4
Understanding user intent is fundamental to delivering relevant search results in e-commerce. However, substantial fraction of real-world queries are under-specified (e.g., "watch"…
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…
What Helps Language Models Predict Human Beliefs: Demographics or Prior Stances?
Joseph Malone, Rachith Aiyappa, Byunghwee Lee +3
Beliefs shape how people reason, communicate, and behave. Rather than existing in isolation, they exhibit a rich correlational structure--some connected through logical dependencie…
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…
A semantic embedding space based on large language models for modelling human beliefs
Byunghwee Lee, Rachith Aiyappa, Yong-Yeol Ahn +2
Beliefs form the foundation of human cognition and decision-making, guiding our actions and social connections. A model encapsulating beliefs and their interrelationships is crucia…
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…
Benchmarking zero-shot stance detection with FlanT5-XXL: Insights from training data, prompting, and decoding strategies into its near-SoTA performance
Rachith Aiyappa, Shruthi Senthilmani, Jisun An +2
We investigate the performance of LLM-based zero-shot stance detection on tweets. Using FlanT5-XXL, an instruction-tuned open-source LLM, with the SemEval 2016 Tasks 6A, 6B, and P-…
Can we trust the evaluation on ChatGPT?
Rachith Aiyappa, Jisun An, Haewoon Kwak +1
ChatGPT, the first large language model (LLM) with mass adoption, has demonstrated remarkable performance in numerous natural language tasks. Despite its evident usefulness, evalua…
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.…
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,…
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…