activity
20192022
most citedIdentifying Nuances in Fake News vs. Satire: Using Semantic and Linguistic Cues

19 citations · 51 across the 9 of their papers we have counts for

collaborators

9 papers

cs.SI2022★ 5 cited

Facebook's Architecture Undermines Vaccine Misinformation Removal Efforts

David A. Broniatowski, Jiayan Gu, Amelia M. Jamison +2

Misinformation promotes distrust in science, undermines public health, and may drive civil unrest. Vaccine misinformation, in particular, has stalled efforts to overcome the COVID-…

cs.CL2022★ 1 cited

Applying Word Embeddings to Measure Valence in Information Operations Targeting Journalists in Brazil

David A. Broniatowski

Among the goals of information operations are to change the overall information environment vis-á-vis specific actors. For example, "trolling campaigns" seek to undermine the credi…

cs.CL2021★ 8 cited

Predicting Directionality in Causal Relations in Text

Pedram Hosseini, David A. Broniatowski, Mona Diab

In this work, we test the performance of two bidirectional transformer-based language models, BERT and SpanBERT, on predicting directionality in causal pairs in the textual content…

cs.CL2020★ 10 cited

A Multi-Modal Method for Satire Detection using Textual and Visual Cues

Lily Li, Or Levi, Pedram Hosseini +1

Satire is a form of humorous critique, but it is sometimes misinterpreted by readers as legitimate news, which can lead to harmful consequences. We observe that the images used in…

cs.CY2020★ 3 cited

The Role of Individual User Differences in Interpretable and Explainable Machine Learning Systems

Lydia P. Gleaves, Reva Schwartz, David A. Broniatowski

There is increased interest in assisting non-expert audiences to effectively interact with machine learning (ML) tools and understand the complex output such systems produce. Here,…

cs.CL2020★ 4 cited

Detecting East Asian Prejudice on Social Media

Bertie Vidgen, Austin Botelho, David Broniatowski +6

The outbreak of COVID-19 has transformed societies across the world as governments tackle the health, economic and social costs of the pandemic. It has also raised concerns about t…

cs.CY2020

Automatically Characterizing Targeted Information Operations Through Biases Present in Discourse on Twitter

Autumn Toney, Akshat Pandey, Wei Guo +2

This paper considers the problem of automatically characterizing overall attitudes and biases that may be associated with emerging information operations via artificial intelligenc…

cs.CL2019★ 19 cited

Identifying Nuances in Fake News vs. Satire: Using Semantic and Linguistic Cues

Or Levi, Pedram Hosseini, Mona Diab +1

The blurry line between nefarious fake news and protected-speech satire has been a notorious struggle for social media platforms. Further to the efforts of reducing exposure to mis…

physics.soc-ph2019★ 1 cited

Health Wars and Beyond: The Rapidly Expanding and Efficient Network Insurgency Interlinking Local and Global Online Crowds of Distrust

N. F. Johnson, N. Velasquez, N. Johnson Restrepo +4

We present preliminary results on the online war surrounding distrust of expertise in medical science -- specifically, the issue of vaccinations. While distrust and misinformation…