1 citations · 1 across the 6 of their papers we have counts for
7 papers
Linking Extreme Discourse to Structural Polarization in Signed Interaction Networks
Zhijin Guo, Li Zhang, Tyler Bonnet +2
Polarization in online communities is often studied through either language or interaction structure, but the two views are rarely connected in a unified measurement pipeline. Prio…
Constructing Composite Features for Interpretable Music-Tagging
Chenhao Xue, Weitao Hu, Joyraj Chakraborty +5
Combining multiple audio features can improve the performance of music tagging, but common deep learning-based feature fusion methods often lack interpretability. To address this p…
Quantifying Compositionality of Classic and State-of-the-Art Embeddings
Zhijin Guo, Chenhao Xue, Zhaozhen Xu +4
For language models to generalize correctly to novel expressions, it is critical that they exploit access compositional meanings when this is justified. Even if we don't know what…
CrediBench: Building Web-Scale Network Datasets for Information Integrity
Emma Kondrup, Sebastian Sabry, Hussein Abdallah +9
Automatically assessing the credibility of online sources presents an invaluable tool for navigating today's information ecosystem. However, existing approaches either depend on sc…
Medfluencer: A Network Representation of Medical Influencers' Identities and Discourse on Social Media
Zhijin Guo, Edwin Simpson, Roberta Bernardi
In our study, we first constructed a dataset from the tweets of the top 100 medical influencers with the highest Influencer Score during the COVID-19 pandemic. This dataset was the…
Compositional Fusion of Signals in Data Embedding
Zhijin Guo, Zhaozhen Xu, Martha Lewis +1
Embeddings in AI convert symbolic structures into fixed-dimensional vectors, effectively fusing multiple signals. However, the nature of this fusion in real-world data is often unc…