AoIR 2023

Types of Polarisation and Their Operationalisation in Digital and Social Media Research

Axel Bruns, Tariq Choucair, Katharina Esau, Sebastian Svegaard, and Samantha Vilkins

• 19 Oct. 2023 – Paper presented at the AoIR 2023 conference, Philadelphia

Presentation Slides

Abstract

Introduction

Apparently increasing partisanship and polarisation, especially online, poses an urgent threat to societal cohesion in many democratic nations; polarisation is also a critical geopolitical concern when actively promoted by bad-faith actors to undermine citizens’ trust in democratic institutions. But not all forms of partisanship and polarisation are inherently pernicious and destructive: milder forms of partisanship also motivate civic participation, constructive political debate, and policy advancement (Le Bas, 2018; McLaughlin, 2018; Mouffe, 1993). This raises complex questions about when polarisation shifts from constructive to destructive; whether this is linked with a move from issue-based, ideological polarisation to identity-based, affective polarisation; and at what point such problematic developments should be countered with active initiatives to depolarise.

Digital communication research provides new opportunities for studying polarisation in terms of traceable interactions and scale, but adds further complexity to an already challenging concept. In this paper, we draw on literature from political science and media and communication studies, concluding that much of the extant research studies polarisation without sufficiently conceptualising it (cf. Kubin & von Sikorski, 2021). This lack of conceptual definition is reflective of disagreements in these fields about what counts as polarisation and about how to assess its extent and impacts. This can lead to substantial problems when operationalising the concept of polarisation in digital media research. Key problems include the conflation of different forms of polarisation, the unquestioned adoption of technologically determinist perspectives, and the over-diagnosis of polarisation as destructive and static.

Building upon existing literature from political science and media and communication studies, we argue for a better demarcation of distinct concepts and definitions in the study of political polarisation as a threat to democracy. We describe the latter phenomenon as destructive political polarisation, in contradistinction from milder and more benign forms of political partisanship. Reviewing the diverse range of polarisation types identified in the literature across both fields, we highlight their key attributes and outline methodological approaches to their operationalisation in mixed-methods research that draws on the quantitative and qualitative analysis of digital trace data.

Polarisation and Its Definitions

Polarisation has gained a negative connotation due to widespread popular and media concerns that societies are becoming increasingly divided, or polarised, in a way that is destructive for democracies. In popular use, the term builds on a blurry definition that encompasses a spectrum from mild political disagreement to outright hostility, and often carries an a priori negative or destructive connotation. By contrast, the social sciences have historically used 'polarisation' in a neutral sense to refer to divisions between societal groups. These divisions can be understood as motivated by different attributes (e.g., ideologies, positions, issues, identities, values, affect, emotions), as operating at different levels (macro, meso, micro), and as focussing on different actors (e.g., politicians, political parties, citizens, journalists, media outlets).

Our full paper works through these definitions of polarisation and their key identified attributes, and outlines how they can be operationalised in digital media research. For instance, ideological polarisation can be understood as the distance between positions on one or more specific policy issues (DiMaggio et al., 1996; Fiorina & Abrams, 2008); traditional definitions in political science focus on elite or mass polarisation through political ideology, capturing (a) the level of agreement or disagreement with specific positions on political or societal issues; or (b) the placement in a broader ideological spectrum. In digital media, this may be investigated through computational or manual analyses of how a diverse range of mainstream or niche media outlets cover and frame the same issues, in terms of their language, tone, sourcing practices, and overall coverage choices (cf. Feldman et al., 2017); additionally, it is possible to trace how social media users in turn share and engage with such material in their own discussions (Giglietto et al., 2019).

But political polarisation can also be understood through concepts other than ideology. Affective polarisation is furthered through positive or negative sentiment expressed towards members of in- and outgroups, resulting in extreme cases in hatred and contempt towards outgroups (e.g., Iyengar et al., 2012; Mason, 2015; Hobolt et al., 2021). Some empirical studies suggest that such affective polarisation can increase even while ideological differences remain static (e.g., Iyengar et. al., 2012; Lelkes, 2016). Such polarisation is thus defined by hostility towards out-group members, and solidarity with one’s own ingroup; notwithstanding the limits of simple computational sentiment analysis as applied to short-form social media texts, such discursive patterns can be assessed and analysed qualitatively and quantitatively through a combination of manual and automated evaluation of affective language and audiovisual components in social media discussions (e.g. Yarchi et al., 2021).

Further, it is also possible to evaluate networks of communication to determine the patterns of interaction between the various discursive groups, in order to examine what Yarchi et al. (2021) term interactional polarisation. This approach is exemplified by studies of climate change discussions on Twitter (Williams et al., 2015) and Reddit (Treen et al., 2022). Polarisation could be defined here simply by the absence of interaction between opposing sides, yet this may represent an oversimplification: as studies such as Williams et al.’s analysis of climate change hashtags on Twitter show, the various communicative affordances of specific platforms (here, @mentions, retweets, and following) may be used in diverging ways to attack, support, connect, and otherwise engage in constructive or destructive ways with in- and outgroup members (also cf. Giglietto et al., 2019). Network analysis, then, can point to distinct patterns of interaction with different groups, but only a further analysis of the content of such interactions will determine their positive or negative valence.

This introduction to three major types of polarisation is far from exhaustive, of course; we will discuss other possible definitions in the full paper, and outline how they may be operationalised in applied digital media research. Further, the approaches we have sketched out here may be employed at varying levels of specificity: in the context of distinct issues (e.g. a momentary political event or crisis); of longer-term debates (e.g. of major themes like climate change or minority rights); or even across multiple themes (e.g. to examine whether in- and outgroup patterns remain stable independent of the specific issues at hand).

Identifying Destructive Polarisation

Finally, a key aim of our work is also to determine whether and when the patterns of polarisation that may be observed in empirical analysis should be seen as inherently problematic. McCoy et al. (2018) argue that, although some political and societal polarisation is beneficial to a functioning democracy (e.g., by enabling political parties to define their distinct positions on key issues and thereby offer a clear choice to electors), once a level of “severe polarization” is reached democratic societies will struggle to maintain productive political processes.

Building on these ideas, we therefore propose a set of criteria for what we describe as destructive political polarisation. We suggest that the following key elements may serve as indicators of destructive polarisation in online communication: (a) breakdown of communication between opposing groups; (b) discrediting and dismissal of oppositional information; (c) erasure of complexities in the discussion of issues; (d) disproportionate space for and attention to extreme voices; (e) exclusion of opposing views through appeals to emotion. This is not intended to represent an exhaustive or definitive list, nor do all these elements need to be present in any one case for polarisation to be destructive. However, we posit that if one of these elements is present, it is likely that others are as well, as they are related and connected to each other in complex ways. The conceptual and methodological considerations presented in our paper make a substantial contribution to the identification of these destructive tendencies in digital and social media communication, and thus also serve as a first step towards addressing such problematic dynamics.

References

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