scholarly journals Political Partisanship and Anti-Science Attitudes in Online Discussions about COVID-19 (Preprint)

Author(s):  
Ashwin Rao ◽  
Fred Morstatter ◽  
Minda Hu ◽  
Emily Chen ◽  
Keith Burghardt ◽  
...  
2020 ◽  
Author(s):  
Ashwin Rao ◽  
Fred Morstatter ◽  
Minda Hu ◽  
Emily Chen ◽  
Keith Burghardt ◽  
...  

BACKGROUND The novel coronavirus pandemic continues to ravage communities across the US. Opinion surveys identified importance of political ideology in shaping perceptions of the pandemic and compliance with preventive measures. OBJECTIVE The aim of this study was to measure political partisanship and anti-science attitudes in the discussions about the pandemic on social media, as well as their geographic and temporal distribution. METHODS We analyze a large set of tweets related to the pandemic collected between January and May of 2020 and develop methods to classify the ideological alignment of users along the moderacy (hardline vs moderate), political (liberal vs conservative) and science (anti-science vs pro-science) dimensions. RESULTS We find that polarization along the science and political dimensions are correlated. Moreover, politically moderate users are more aligned with the pro-science views, while hardline users are more aligned with anti-science views. Contrary to expectations, we do not find that polarization grows over time; instead, we see increasing activity by moderate pro-science users. We also show that anti-science conservatives tend to tweet from the Southern and Northwestern US, while anti-science moderates from the Western states. The proportion of anti-science conservatives are found to correlate with COVID-19 cases. CONCLUSIONS Our findings shed light on the multi-dimensional nature of polarization, and the feasibility of tracking polarized opinions about the pandemic across time and space through social media data.


2021 ◽  
Author(s):  
J. Hunter Priniski

Despite widespread communication of the health risks associated with the COVID-19 virus, many Americans underestimated its risks and were antagonistic regarding preventative measures. Political partisanship has been linked to diverging attitudes towards the virus, but the cognitive processes underlying this divergence remain unclear. Bayesian models fit to data gathered through two preregistered, online surveys administered before (March 13, 2020, N = 850) and during the first-wave (April-May, 2020, N = 1610) of cases in the United States, reveal two preexisting forms of distrust––distrust in Democratic politicians and in medical scientists––that drove initial skepticism about the virus. During the first-wave of cases, additional factors came into play, suggesting that skeptical attitudes became more deeply embedded within a complex network of auxiliary beliefs. These findings highlight how mechanisms that enhance cognitive coherence can drive anti-science attitudes.


2021 ◽  
Vol 13 (6) ◽  
pp. 160
Author(s):  
Minda Hu ◽  
Ashwin Rao ◽  
Mayank Kejriwal ◽  
Kristina Lerman

Successful responses to societal challenges require sustained behavioral change. However, as responses to the COVID-19 pandemic in the US showed, political partisanship and mistrust of science can reduce public willingness to adopt recommended behaviors such as wearing a mask or receiving a vaccination. To better understand this phenomenon, we explored attitudes toward science using social media posts (tweets) that were linked to counties in the US through their locations. The data allowed us to study how attitudes towards science relate to the socioeconomic characteristics of communities in places from which people tweet. Our analysis revealed three types of communities with distinct behaviors: those in large metro centers, smaller urban places, and rural areas. While partisanship and race are strongly associated with the share of anti-science users across all communities, income was negatively and positively associated with anti-science attitudes in suburban and rural areas, respectively. We observed that emotions in tweets, specifically negative high arousal emotions, are expressed among suburban and rural communities by many anti-science users, but not in communities in large urban places. These trends were not apparent when pooled across all counties. In addition, we found that anti-science attitudes expressed five years earlier were significantly associated with lower COVID-19 vaccination rates. Our analysis demonstrates the feasibility of using spatially resolved social media data to monitor public attitudes on issues of social importance.


2009 ◽  
Vol 10 (1) ◽  
pp. 4-11
Author(s):  
Susan Sparks ◽  
Lisa Van Horne

Abstract There is an increasing demand for qualified individuals available in our profession. One answer to this crisis is to hire trained speech-language pathology assistants (SLPAs) to assist speech language pathologists (SLPs). Shoreline Community College's SLPA program was created in response to the shortage of fully trained SLPs. The program is designed in strict compliance with ASHA's guidelines (ASHA, 2004). Students attend lectures remotely, complete assigned reading, take quizzes, engage in in-class and online discussions, turn in assignments, and take exams without ever having to commute to the Shoreline campus. This allows students from across the state to complete their education while continuing to live and work in their communities.


Author(s):  
Marlene Kunst

Abstract. Comments sections under news articles have become popular spaces for audience members to oppose the mainstream media’s perspective on political issues by expressing alternative views. This kind of challenge to mainstream discourses is a necessary element of proper deliberation. However, due to heuristic information processing and the public concern about disinformation online, readers of comments sections may be inherently skeptical about user comments that counter the views of mainstream media. Consequently, commenters with alternative views may participate in discussions from a position of disadvantage because their contributions are scrutinized particularly critically. Nevertheless, this effect has hitherto not been empirically established. To address this gap, a multifactorial, between-subjects experimental study ( N = 166) was conducted that investigated how participants assess the credibility and argument quality of media-dissonant user comments relative to media-congruent user comments. The findings revealed that media-dissonant user comments are, indeed, disadvantaged in online discussions, as they are assessed as less credible and more poorly argued than media-congruent user comments. Moreover, the findings showed that the higher the participants’ level of media trust, the worse the assessment of media-dissonant user comments relative to media-congruent user comments. Normative implications and avenues for future research are discussed.


2010 ◽  
Author(s):  
Tianyi Zhang ◽  
Matthew J. Koehler ◽  
Fei Gao

2020 ◽  
Vol 149 (3) ◽  
pp. 407-418 ◽  
Author(s):  
Leor Zmigrod ◽  
Peter Jason Rentfrow ◽  
Trevor W. Robbins

2008 ◽  
Vol 11 (4) ◽  
Author(s):  
Katrina A. Meyer

Thirteen students in a graduate-level course on Historical and Policy Perspectives in Higher Education held face-to-face and online discussions on five controversial topics: Diversity, Academic Freedom, Political Tolerance, Affirmative Action, and Gender. Students read materials on each topic and generated questions for discussion that were categorized by Bloom’s taxonomy so that the level of questions in the two discussion settings would be closely parallel. Upon completion of each discussion, they answered questions that addressed depth and length of the discussion, ability to remember, and a self-assessment of how the student learned. Students’ assessments show a consistent preference for the face-to-face discussion but a small number of students preferred the online setting. However, what is perhaps more interesting is a minority of approximately one-third of the students who perceived no difference between the settings, or that the two settings were perhaps complementary.


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