Explicit civility (Online Discussions/Discussion Quality)
Authors: Heinbach Dominique 
Published: November 2022

Explicit civility or respect is a key dimension to assess the (deliberative) quality of online discussions. In contrast to operationalizations that address civility through the mere absence of incivility or offensive language, this construct measures explicit indicators for respect, such as acknowledgements, endorsement, and explicit valuation.
Field of application/Theoretical foundation
Most studies on online discussions draw on deliberative norms to measure the quality of their discourse (e.g., Esau et al., 2017; Friess et al., 2021; Rowe, 2015; Ziegele et al., 2020; Zimmermann, 2017). Deliberation is an important concept for the study of (political) online discussions and consists of a fair and respectful exchange of arguments between participants who are deemed as equals (Graham & Witschge, 2003; Ziegele et al., 2020). Mutual respect and appreciation of one another are considered fundamental assets of a democratic society (Papacharissi, 2004). A minimum level of respect ensures the mutual acknowledgement of participants as free and equal members of society and hence is a requirement for deliberation (Habermas, 2007; Steiner, 2012; Ziegele et al., 2020).

References/Combination with other methods
Besides quantitative content analyses, the (deliberative) quality of online discussions is examined with qualitative content analyses and discourse analyses (Graham & Witschge, 2003; Price & Capella, 2002). Furthermore, perceptions of civility and incivility are investigated with qualitative interviews and focus groups (Bormann, 2022; Engelke, 2019; Ziegele, 2016), surveys (Kenski et al., 2020; Stryker et al., 2016) and experimental designs (Muddiman, 2017; Ziegele et al., 2019).
Cross-references
Explicit civility is one of five dimensions of deliberative quality in this database written by the same author. Accordingly, there are overlaps with the entries on interactivity, inclusivity, rationality, and storytelling regarding theoretical background, references/combinations with other methods, and some example studies.

Information on Heinbach & Wilms (2022)
Authors: Dominique Heinbach & Lena K. Wilms (Codebook by Dominique Heinbach, Marc Ziegele, & Lena K. Wilms)
Research question: Which attributes differentiate moderated from unmoderated comments?
Object of analysis: The quantitative content analysis was based on a stratified random sample of moderated and not moderated comments (N = 1.682) from the German online participation platform “#meinfernsehen2021” [#myTV2021], a citizen participation platform to discuss the future of public broadcasting in Germany.
Time frame of analysis: November 24, 2020 to March 3, 2021
Info about variables
Level of analysis: User comment
Variables and reliability: see Table 1
Values: All variables were coded on a four-point scale (1 = clearly not present; 2 = rather not present; 3 = rather present; 4 = clearly present). Detailed explanations and examples for each value are provided in the Codebook (in German).
Codebook: in the appendix of this entry (in German)
Table 1: Variables and reliability (Heinbach & Wilms, 2022)

Dimension

Measure

Definition

Krippendorff’s α
(n = 159, 3 coders)

Explicit
respect

Polite salutation

Does the comment contain formulations of polite salutations, greetings or farewell phrases, e.g., “Dear …”, “Have a good weekend”?

.80

Expression of respect

Does the comment contain appreciation, approval, praise, or acknowledgements, e.g, “Kudos!”, “You are doing a great job, “Thank you”, “I respect your opinion“?

.71

Information on Stromer-Galley (2007)
Author: Jennifer Stromer-Galley
Research question: The aim of the paper was developing a coding scheme for academics and practitioners of deliberation to systematically measure what happens during group deliberations (p. 1; p. 7).
Object of analysis: The author conducted a secondary analysis of online group discussions (23 groups with 5-12 participants) in an experiment called “The Virtual Agora Project” at Carnegie Mellon Unversitiy in Pittsburgh, Pennsylvania. Participants attended the discussions from dormitory rooms that were equipped with a computer, headphones, and microphone. The group discussions were recorded and transcribed for analysis (pp. 7-8). Although strictly speaking the study does not analyze media content, the coding scheme has provided the basis for numerous other studies on the deliberative quality of online discussions (e.g., Rowe, 2015; Stroud et al., 2015; Ziegele et al., 2020).
Time frame of analysis: Three weeks in July 2004 (p. 7).
Info about variables
Level of analysis: Social talk was measured on the level of the thought. Coders segmented each speaking contribution into thought units before coding the categories. “A thought is defined as an utterance (from a single sentence to multiple sentences) that expresses an idea on a topic. A change in topic signaled a change in thought. A second indicator of a change in thought was a change in the type of talk. The distinct types of talk that this coding captured were the following: talk about the problem of public schools, talk about the process of the talk, talk about the process of the deliberation, and social talk” (p. 9).
Variables and values: see Table 2
Reliability: Reliability scores for social talk are not provided.
Codebook: in the appendix (pp. 22-33)
Table 2: Variables and values (Stromer-Galley, 2007, p. 9; pp. 26-27).

Variable

Description

Value

Definition

Social talk

Social talk is talk that brings the strangers together by building social bonds, including salutations, praise, and apologies.

Salutations

Statements of welcome, greeting, hello, and good bye, see you later, and the like.

Apologies

Statements of apology: I’m sorry, and ‘I hope’ statements, such as “I hope I haven’t been too obnoxious.” Includes statements of reflection of how the participant performed in the group (likely comes at the end of the group’s discussion): “I hope my few ideas did get across.”

Praise

Includes thank you, you’re welcome, as well as praise for other individuals or the group (“you’ve been a good group.” I’ve really enjoyed myself,” “this has been fun”) Praise in the service of an argument about the problem is coded as a problem thought (“I want to commend Sally for volunteering at her school. We need more people to be volunteers”).

ChitChat

Thought statements that are not on topic relative to the deliberation. These could be jokes or puns (but not as they relate to the problem of schools), social chit chat about the weather, and the like.

Information on Zimmermann (2017)
Author: Tobias Zimmermann
Research question: Which role do online reader comments play for a deliberative-democratic understanding of a digital public sphere? (p. 11)
Object of analysis: To compare discursive participation online and offline, the author conducted a full-sample content analysis of online reader comments (N = 1.176) and letters to the editor (N = 381) from German local newspapers on three similar conflicts in local politics concerning the renaming of streets and squares. Because the coding scheme was based on the discourse quality index (DQI), only contributions that contained a demand were included in the analysis, that is, “a proposal on what decision should or should not be made” Steenbergen et al., 2003, p. 27). Only then, a speech act is considered relevant from a discourse ethics perspective.
Time frame of analysis: June 2012 to May 2013
Info about variables
Variables: For the variable respect towards groups, the author extends the respect variable of the Discourse Quality Index (DQI, Steenbergen et al., 2003) by adding anti-democratic behavior following Papacharissi (2004). Besides the ordinal variable “respect”, the author measured the dichotomous variable “democratic respect”.
Level of analysis: Individual contribution
Variables and values: see Table 3
Reliability: Intracoder reliability was tested on a subset of 100 comments. The ordinal respect variable exceeded a Krippendorff’s Alpha above .73 (p. 201). The dichotomous variable “democratic respect” that measured if a comment contained anti-democratic behavior or not reached a Krippendorff’s Alpha of .89 (p. 200-201).
Codebook: pp. 159-185 (in German)
Table 3: Variables and values (Zimmermann, 2017, p. 171; p. 189)

Variable

Value

Definition

Respect

Anti-democratic behavior

Only or predominantly statements are made that either contain at least one threat against the democratic system as a whole, use negative stereotypes, or question other individuals’ individual liberty rights.

No respect

This category applies when exclusively or predominantly negative statements about others, but not anti-democratic statements are made.

Implicit respect

There are no explicitly positive or negative statements to others, that is, a comment is neither explicitly respectful nor disrespectful.

Balanced respect

Both positive and negative statements in relation to others are expressed in the same degree.

Explicit respect

This category is applied when there is at least one explicitly positive statement regarding others and no negative statements, or if the positive statement clearly dominates the negative.

Democratic respect

Anti-democratic behavior

Only or predominantly statements are made that either contain at least one threat against the democratic system as a whole, use negative stereotypes, or question other individuals’ individual liberty rights.

Democratic respect

Anti-democratic behavior does not occur.

Example studies
Heinbach, D. & Wilms, L. K. (2022): Der Einsatz von Moderation bei #meinfernsehen2021 [The deployment of moderation at #meinfernsehen2021]. In: F. Gerlach, C. Eilders & K. Schmitz (Eds.): #meinfernsehen2021. Partizipationsverfahren zur Zukunft des öffentlich-rechtlichen Fernsehens. Baden-Baden: Nomos.
Stromer Galley, J. (2007). Measuring Deliberation's Content: A Coding Scheme. Journal of Public Deliberation, 3(1), Article 12.
Zimmermann, T. (2017). Digitale Diskussionen: Über politische Partizipation mittels Online-Leserkommentaren [Digital discussions: On political participation trough online reader comments]. Edition Politik: Bd. 44. transcript Verlag. http://www.content-select.com/index.php?id=bib_view&ean=9783839438886
Further references
Bormann, M. (2022). Perceptions and Evaluations of Incivility in Public Online Discussions—Insights From Focus Groups With Different Online Actors. Frontiers in Political Science, 4, Article 812145. https://doi.org/10.3389/fpos.2022.812145
Engelke, K. M. (2019). Enriching the Conversation: Audience Perspectives on the Deliberative Nature and Potential of User Comments for News Media. Digital Journalism, 8(4), 1–20. https://doi.org/10.1080/21670811.2019.1680567
Esau, K., Friess, D. & Eilders, C. (2017). Design Matters! An Empirical Analysis of Online Deliberation on Different News Platforms. Policy & Internet, 9(3), 321–342. https://doi.org/10.1002/poi3.154
Friess, D., Ziegele, M. & Heinbach, D. (2021). Collective Civic Moderation for Deliberation? Exploring the Links between Citizens’ Organized Engagement in Comment Sections and the Deliberative Quality of Online Discussions. Political Communication, 38(5), 624–646. https://doi.org/10.1080/10584609.2020.1830322
Graham, T. & Witschge, T. (2003). In Search of Online Deliberation: Towards a New Method for Examining the Quality of Online Discussions. Communications, 28(2). https://doi.org/10.1515/comm.2003.012
Habermas, J. (2007). Moral consciousness and communicative action (Repr). Polity.
Kenski, K., Coe, K. & Rains, S. A. (2020). Perceptions of Uncivil Discourse Online: An Examination of Types and Predictors: An examination of types and predictors. Communication Research, 47(6), 795–814. https://doi.org/10.1177/0093650217699933
Muddiman, A. (2017). Personal and Public Levels of Political Incivility. International Journal of Communication, 11, 3182–3202.
Papacharissi, Z. (2004). Democracy online: civility, politeness, and the democratic potential of online political discussion groups. new media & society, 6(2), 259–283. https://doi.org/10.1177/1461444804041444
Price, V. & Cappella, J. N. (2002). Online deliberation and its influence: The Electronic Dialogue Project in Campaign 2000. IT&Society, 1(1), 303–329. https://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.9.5945&rep=rep1&type=pdf
Rowe, I. (2015). Deliberation 2.0: Comparing the Deliberative Quality of Online News User Comments Across Platforms. Journal of Broadcasting & Electronic Media, 59(4), 539–555. https://doi.org/10.1080/08838151.2015.1093482
Steenbergen, M. R., Bächtiger, A., Spörndli, M., & Steiner, J. (2003). Measuring Political Deliberation: A Discourse Quality Index. Comparative European Politics, 1(1), 21–48. https://doi.org/10.1057/palgrave.cep.6110002
Steiner, J. (2012). The Foundations of Deliberative Democracy. Cambridge University Press. https://doi.org/10.1017/CBO9781139057486
Stroud, N. J., Scacco, J. M., Muddiman, A., & Curry, A. L. (2015). Changing Deliberative Norms on News Organizations' Facebook Sites. Journal of Computer-Mediated Communication, 20(2), 188–203. https://doi.org/10.1111/jcc4.12104
Stryker, R., Conway, B. A. & Danielson, J. T. (2016). What is political incivility? Communication Monographs, 83(4), 535–556. https://doi.org/10.1080/03637751.2016.1201207
Ziegele, M. (2016). Nutzerkommentare als Anschlusskommunikation: Theorie und qualitative Analyse des Diskussionswerts von Online-Nachrichten [The Discussion Value of Online News. An Analysis of User Comments on News Platforms]. Springer VS.
Ziegele, M., Naab, T. K. & Jost, P. (2020). Lonely together? Identifying the determinants of collective corrective action against uncivil comments. New Media & Society, 22(5), 731-751. https://doi.org/10.1177/1461444819870130
Ziegele, M., Quiring, O., Esau, K. & Friess, D. (2020). Linking News Value Theory With Online Deliberation: How News Factors and Illustration Factors in News Articles Affect the Deliberative Quality of User Discussions in SNS’ Comment Sections. Communication Research, 47(6), 860-890. https://doi.org/10.1177/0093650218797884