Attribute Agenda Setting on Twitter and the Wall Street Journal: The Case of Congresswoman Ilhan Omar

• Published in: Review of Middle East studies (Tucson, Ariz.) Vol. 55; no. 1; pp. 35 - 55
• Main Authors: Alkazemi, Mariam, Oladi Ghadikolai, Sameneh, Oetjens, Marilynn, Boone, Edward L.
• Format: Journal Article
• Language: English
• Published: New York, USA Cambridge University Press 01-06-2021; Middle East Studies Association of North America (MESA)
• Subjects: Immigrants; Multiculturalism & pluralism; Muslims; Omar, Ilhan; Oppression; Social networks; SPECIAL FOCUS: SPOTLIGHT ON PEDAGOGICAL PERSPECTIVES AND THE POLITICS OF REPRESENTATION; Tlaib, Rashida; Trump, Donald J; Women; Xenophobia; United States > US; Agenda setting; Twitter; Identity politics; Islamophobia; content analysis
• ISSN: 2151-3481; 2329-3225
• DOI: 10.1017/rms.2021.31

This study examines attributes associated with U.S. Congresswoman Ilhan Omar. Omar's unique intersectionality of identities as a Black, immigrant, Muslim woman presents a rich case study for an examination of attribute agenda setting. A sample of Tweets, all Wall Street Journal articles referencing the congresswoman, and Google searches were obtained for the hashtags (“IlhanOmar,” “GoBack,” and “WelcomeHome.”) from May 2019 to January 2020. The Tweets and articles were then coded for a variety of dimensions. Analysis of the frequencies of words associated with the coding and the hashtags showed that the majority of the messages were negative despite the hashtag for which they were collected. A cross-correlation time series analysis showed that articles and editorials published by the Wall Street Journal predicted spikes in Google searches and Twitter messages. This article pinpoints underlying sociological phenomena about the representations of gender, race, religion, and immigration status to show the arguments that link attributes of Ilhan Omar together on Twitter.