About Me

I’m a computational social scientist who studies the media information ecosystem.

I’m currently a postdoctoral researcher at Northwestern University in the Kellogg School of Management. I received my PhD in Computer and Information Science from the University of Pennsylvania, where I worked with Duncan Watts and Chris Callison-Burch.

My research focuses on using computational approaches to study news production systematically and at scale. I combine LLMs with large-scale data infrastructure to analyze which topics and events news outlets choose to cover (or ignore), how they frame their coverage, and whose voices they amplify in their reporting.

Here is my CV.

News

09/2026: Our Media Bias Detector paper was published in Science Advances! Check out the paper, browse the dashboard, and read us talk about its broader impact!

08/2026: I defended my PhD and will be starting my postdoc at Northwestern!

04/2025: I’m co-chairing the 2025 NAACL Student Research Workshop (SRW). See you all in Albuquerque!

07/2024: We organized the first-ever joint SICSS and IC2S2 at Penn. We hope you all enjoyed your time in Philadelphia!

12/2023: I received an Outstanding Reviewer Award from EMNLP 2023!

Papers

• The Media Bias Detector: A Framework for Annotating and Analyzing the News.
  Samar Haider, Amir Tohidi, Jenny S. Wang, Timothy Dörr, David M. Rothschild, Chris Callison-Burch, Duncan J. Watts.
  Science Advances, eaea7456, 2026.

• Selective Facts Can Be As Persuasive As Falsehoods.
  Jenny Allen, Amir Tohidi, Samar Haider, David Rothschild, Duncan J. Watts.
  R&R at Science Advances, 2026.

• Rethinking News Framing with Large Language Models.
  Amir Tohidi, Samar Haider, Duncan J. Watts.
  Scientific Reports, 2025.

• Media Bias Detector: Designing and Implementing a Tool for Real-Time Selection and Framing Bias Analysis in News Coverage.
  Jenny Wang, Samar Haider, Amir Tohidi, Anushkaa Gupta, Yuxuan Zhang, Chris Callison-Burch, David Rothschild, Duncan J. Watts.
  Proceedings of the ACM Conference on Human Factors in Computing Systems (CHI), 2025.

• Multilingual Retrieval Augmented Generation for Culturally-Sensitive Tasks: A Benchmark for Cross-lingual Robustness.
  Bryan Li, Fiona Luo, Samar Haider, Adwait Agashe, Siyu Li, Runqi Liu, Muqing Miao, Shriya Ramakrishnan, Yuan Yuan, Chris Callison-Burch.
  Findings of the Association for Computational Linguistics (ACL), 2025.

• This Land is {Your, My} Land: Evaluating Geopolitical Bias in Language Models through Territorial Disputes.
  Bryan Li, Samar Haider, Chris Callison-Burch.
  Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), 2024.

• BordIRlines: A Dataset for Evaluating Cross-lingual Retrieval Augmented Generation.
  Bryan Li, Samar Haider, Fiona Luo, Adwait Agashe, Chris Callison-Burch.
  Workshop on Advancing Natural Language Processing for Wikipedia (WikiNLP) at EMNLP, 2024.

• Vizard: Improving Visual Data Literacy with Large Language Models.
  Rubab Zahra Sarfraz, Samar Haider.
  International Workshop on Big Data Visual Exploration and Analytics (BigVis) at VLDB, 2024.

• Detecting Social Media Manipulation in Low-Resource Languages.
  Samar Haider, Luca Luceri, Ashok Deb, Adam Badawy, Nanyun Peng, Emilio Ferrara.
  Companion Proceedings of the ACM Web Conference (WWW), 2023.

• Digital Civic Participation and Misinformation during the 2020 Taiwanese Presidential Election.
  Ho-Chun Herbert Chang, Samar Haider, Emilio Ferrara.
  Media and Communication, 2021.

• Urdu Word Embeddings.
  Samar Haider.
  International Conference on Language Resources and Evaluation (LREC), 2018.