Talking Past Each Other on Twitter: Thematic, Event, and Temporal Divergences in Polarized Partisan Expression on Immigration

ABSTRACT

Extending literature on political polarization and political expression, we study patterns of polarized expression by vocal partisans from opposing camps on social media. Specifically, we argue that polarized partisan expression can be characterized by three divergences: 1) different thematic emphases on the same issue; 2) response to different real-world events on the same issue; and 3) a temporal disconnect at the aggregate level. Highlighting how online expression by different partisan groups is animated by discrete concerns and events and exhibits different temporality, the three divergences in polarized partisan expression not only reflect and explain existing polarization concepts but also speak to the epistemological chasm between partisan groups. Our empirical analysis is based on Twitter discussion about the issue of immigration in the U.S. and applies topic modeling and time series analysis. Results demonstrate that liberal and conservative tweets exhibit different thematic emphases, are often spurred by different event features, and remain largely temporally independent, though both Trump’s tweets and emotionally evocative events can draw simultaneous reaction from both sides. These findings suggest that opposing partisan groups not only hold different views on the same issue, but also weave different events and facts about the issue into partisan expression in response to different exogenous factors. In short, they “talk past each other.” These polarized partisan expression patterns indicate a splintered public sphere, a concerning quality for deliberative democracy.

KEYWORDS:

• Polarization
• partisanship
• partisan expression
• social media
• immigration

Disclosure Statement

No potential conflict of interest was reported by the author(s).

Data Availability Statement

Data is available upon request.

Open Scholarship

This article has earned the Center for Open Science badge for Open Materials. The materials are openly accessible at https://osf.io/3wqe4/

Supplementary material

Supplemental data for this article can be accessed on the publisher’s website at https://doi.org/10.1080/10584609.2023.2263400.

Notes

1. We use conservatives/liberals from here on because 1) partisan-ideological sorting in the U.S. has resulted in the alignment of liberals with the Democratic Party and conservatives with the Republican Party; and 2) conservatives/liberals are more generalizable to the global context.

2. According to agenda-setting research, an issue is “whatever is in contention among a relevant public” (Lang & Lang, 1991, p.281), a definition that we adopt in this study. As discussed in the literature review, a “thematic emphasis” refers to an interpretive lens and the resulting semantic coherence in expression. As such, issues are what the first-level agenda-setting research is mainly concerned about, while thematic emphases are largely equivalent to frames or attributes in the second-level agenda-setting research (Ceron, Curini & Iacus, 2016).

3. https://ballotpedia.org/Timeline_of_federal_policy_on_immigration,_2017-2020

4. For international sources, we referred to U.S. editions or coverage.

5. Due to the lack of pro-immigration events concerning family separation and refugee admissions, the “Family Separation – allow” and “Refugee Admissions – allow” variables were dropped from the analysis.

Additional information

Notes on contributors

Xiaoya Jiang

Xiaoya Jiang is a PhD candidate at the School of Journalism & Mass Communication, University of Wisconsin-Madison. She studies public opinion using computaional approaches.

Yini Zhang

Yini Zhang (Ph.D. University of Wisconsin-Madison) is an assistant professor in the Department of Communication at the University at Buffalo, State University of New York. She studies social media and political communication, using computational methods.

Jisoo Kim

Jisoo Kim is a PhD candidate at the School of Journalism & Mass Communication, University of Wisconsin-Madison. She studies political polarization and politicization in relation to the communication environment.

Jon Pevehouse

Jon Pevehouse is Vilas Distinguished Professor of Political Science in the Department of Political Science, University of Wisconsin Madison.

Dhavan Shah

Dhavan V. Shah is the Louis A. & Mary E. Maier-Bascom Professor at the University of Wisconsin-Madison, where he is Director of the Mass Communication Research Center (MCRC) and Scientific Director in the Center for Health Enhancement System Studies (CHESS).