Partisan US News Media Representations of Syrian Refugees

Keyu Chen, Marzieh Babaeianjelodar, Yiwen Shi, Kamila Janmohamed, Rupak Sarkar, Ingmar Weber, Thomas Davidson, Munmun De Choudhury, Jonathan Huang, Shweta Yadav, Ashiqur Khudabukhsh, Chris T Bauch, Preslav Nakov, Orestis Papakyriakopoulos, Koustuv Saha, Kaveh Khoshnood, Navin Kumar

Research output: Contribution to journalConference articlepeer-review


We investigate how representations of Syrian refugees (2011-2021) differ across US partisan news outlets. We analyze 47,388 articles from the online US media about Syrian refugees to detail differences in reporting between left- and right-leaning media. We use various NLP techniques to understand these differences. Our polarization and question answering results indicated that left-leaning media tended to represent refugees as child victims, welcome in the US, and right-leaning media cast refugees as Islamic terrorists. We noted similar results with our sentiment and offensive speech scores over time, which detail possibly unfavorable representations of refugees in right-leaning media. A strength of our work is how the different techniques we have applied validate each other. Based on our results, we provide several recommendations. Stakeholders may utilize our findings to intervene around refugee representations, and design communications campaigns that improve the way society sees refugees and possibly aid refugee outcomes.
Original languageEnglish (US)
Pages (from-to)103-113
JournalProceedings of the International AAAI Conference on Web and Social Media
StatePublished - Jun 2 2023
Externally publishedYes


  • Credibility of online content
  • demographic/gender/age identification
  • topic recognition
  • Text categorization
  • Centrality/influence of social media publications and authors
  • Web and Social Media


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