2020
DOI: 10.1177/0032321719894708
|View full text |Cite
|
Sign up to set email alerts
|

What Kind of Disagreement Favors Reason-Giving? Analyzing Online Political Discussions across the Broader Public Sphere

Abstract: This study adopts a systemic approach, focusing on real-world online discussions in legislative-, media-, and activist-based forums, to explore a set of factors that affects reasoned disagreement in digital environments. While conventional analysis investigates the effects of disagreement on civic and political participation, this study unpacks forms of disagreement that retain a principled link with reason-giving. Our findings demonstrate that context matters for shaping online communication, but that other v… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
1
1

Citation Types

1
4
0
1

Year Published

2020
2020
2023
2023

Publication Types

Select...
6
3

Relationship

0
9

Authors

Journals

citations
Cited by 15 publications
(6 citation statements)
references
References 75 publications
(165 reference statements)
1
4
0
1
Order By: Relevance
“…Second, the integrative complexity of online user comments was higher in arenas that are used primarily for issue- rather than preference-driven discussions. This supports prior research that found opinion diversity and disagreement to encourage the extent of justifications in such posts (Maia et al 2020; Zhang et al 2013). It suggests that the “imagined affordances” (Nagy and Neff 2015: 1) of different discussion arenas indeed frame how debate participants primarily use these spaces in accordance with how they think they are expected to act.…”
Section: Discussionsupporting
confidence: 89%
See 1 more Smart Citation
“…Second, the integrative complexity of online user comments was higher in arenas that are used primarily for issue- rather than preference-driven discussions. This supports prior research that found opinion diversity and disagreement to encourage the extent of justifications in such posts (Maia et al 2020; Zhang et al 2013). It suggests that the “imagined affordances” (Nagy and Neff 2015: 1) of different discussion arenas indeed frame how debate participants primarily use these spaces in accordance with how they think they are expected to act.…”
Section: Discussionsupporting
confidence: 89%
“…Debates are characterized by in-group acknowledgment (Freelon 2015) and polarization (Yarchi et al 2020)—also in non-U.S. contexts such as Germany and Australia, where Twitter users “are substantially more likely to engage with supportive rather than oppositional networks” (Vaccari et al 2016: 6; Bruns et al 2017). Likewise, user comments on the Facebook pages of partisan civic organizations were found to contain strongly homogeneous views (Maia et al 2020) along with high levels of negative emotions (Esau et al 2020). In addition, partisan media commonly make their audience dislike the opposition (Levendusky 2013).…”
Section: Theorymentioning
confidence: 99%
“…While hashtags could potentially bring together individuals with different views, in reality, they primarily integrate those with similar positions. Likewise, research suggests that the Facebook pages of partisan collective actors and alternative media are used primarily for discussions among like-minded people (Maia & Rezende, 2016; Maia et al, 2021). In contrast, the website comment sections and Facebook pages of mainstream news media assemble a readership base that is connected by an interest in the topic of the original article (Freelon, 2015) and whose political views have been shown to be rather diverse (Nelson & Webster, 2017).…”
Section: Theorymentioning
confidence: 99%
“…Research shows that frequent posters have a particular habit to support their statements with reasons (Graham and Wright, 2014) and that the justification levels are higher in user-generated discussions in countries with liberal than with polarized pluralist media systems (Ruiz et al, 2011). Generally, online debaters ground their assertions more regularly in light of opinion diversity and disagreement (Maia et al, 2020).…”
Section: Theorymentioning
confidence: 99%