Conference Agenda

T2: GOR Thesis Award 2020 Competition II
Thursday, 10/Sep/2020:
11:40 - 1:00

Session Chair: Frederik Funke, Dr. Funke SPSS- & R-Trainings & LimeSurvey GmbH, Germany


The Digital Architectures of Social Media: Platforms and Participation in Contemporary Politics

Michael Joseph Bossetta

Lund University, Sweden

Social media platforms (SMPs) influence the communication of virtually all stakeholders in democratic politics. Politicians and parties campaign through SMPs, media organizations use them to distribute political news, and many citizens read, share, and debate political issues across multiple social media accounts. When assessing the political implications of these practices, scholars have traditionally focused on the commonalities of SMPs, rather than their differences. The implications of this oversight are both theoretical and methodological. Theoretically, scholars lack an overarching conceptual framework to inform cross-platform research designs. As a result, the operationalization of social media variables across platforms is often inconsistent and incomparable, limiting the attribution of platform-specific effects.

This dissertation therefore contributes to the study of digital media and politics by developing a cross-platform theory of platforms’ digital architectures. Digital architectures are defined as the collective suite of technical protocols that enable, constrain, and shape user behavior in a virtual space. The dissertation’s central argument is that the digital architectures of SMPs mediate how users enact political processes through them. Focusing on politicians’ campaigning and citizens’ political participation during elections, I show how political communication processes manifest differently across platforms in ways that can be attributed to their digital architectures. Moreover, I demonstrate how both politicians and citizens manipulate the digital architectures of platforms to further their political agendas during elections.

To mount these arguments, the dissertation adopts a highly conceptual, exploratory, and interdisciplinary approach. Its main theoretical contribution, the digital architectures framework, brings together fragments from literatures spanning archeology, design theory, media studies, political communication, political science, social movements, and software engineering. Methodologically, the study combines qualitative and quantitative methods to address the research questions of four individual research articles (Chapters 4-7). These studies have been published in Information, Communication & Society; Journalism & Mass Communication Quarterly; Language and Politics; and a book chapter in Social Media and European Politics (Palgrave). The main empirical cases included in the dissertation are the 2015 British General Election, the 2016 Brexit Referendum, and the 2016 U.S Presidential Election.

The structure of the dissertation is as follows. Chapter 1 introduces the dissertation’s overarching research questions and design. Chapter 2 situates the digital architectures framework within the existing literature by critiquing existing theoretical approaches to social media and political participation. Chapter 3 outlines the main challenges in studying participation on social media, as well as summarizes the dissertation’s methodological approach. Chapter 4 then presents the digital architectures framework through a systematic, cross-platform comparison of Facebook, Twitter, Instagram, and Snapchat. In this chapter, I illustrate how the digital architectures of these SMPs shaped how American politicians used them for political campaigning in the 2016 U.S. election.

Shifting focus from politics to citizens, Chapter 5 examines how the digital architectures of social media influence citizens’ political participation. Chapter 5 characterizes the various styles and degrees of political participation through SMPs, and it shows how the architectures of Twitter and Facebook lead to different manifestations of online participation in the context of European politics.

Building on the Chapter 5’s conceptual work, Chapters 6 and 7 use digital trace data to empirically investigate citizens’ participation on Twitter and Facebook, respectively. Chapter 6 offers a new theory of online political participation by conceptualizing it as a process, rather than as an activity. Chapter 6 develops a typology of political participation and applies it to citizens’ use of Twitter in the 2015 British General Election. We find that a small number of highly active citizens dominate the political discussion on Twitter, and these citizens tend to promote right-wing, nationalist positions.

Chapter 7 finds similar patterns in citizens’ political participation on Facebook during the 2016 Brexit referendum. Using metadata to chart the commenting patterns of citizens across media and political Facebook pages, Chapter 7 reveals that Leave supporters were much more active in political commentary than Remain supporters. However, this phenomenon is, again, due to a small number of active citizens promoting right-wing, nationalist positions. Few citizens commented on both media and campaign Facebook pages during the referendum, but those who did commented on the media first. This finding, together with the observation that political commentary overwhelmingly took place on media pages, supports the notion that the mainstream media maintain their agenda-setting role on SMPs.

Lastly, Chapter 8 argues that different digital architectures afford varying degrees of publicness, which in turn affects how political participation is actualized across platforms. This chapter, and the thesis, concludes with a discussion of why the digital architectures of social media are critical to consider when assessing social media’s impact on democracy.

Optimizing measurement in Internet-based research: Response scales and sensor data

Tim Kuhlmann

Universität Siegen, Germany

The present PhD thesis lies within the area of Internet-based research; specifically it is concerned with Internet-based assessment via questionnaires and smartphones. The thesis investigates the influence of response scales and objective sensor data from smartphones on the data gathering process and data quality. Internet-based questionnaires and tests are becoming increasingly common in psychology and other social sciences (Krantz & Reips, 2017; Wolfe, 2017). It is therefore important, for researchers and practitioners alike, to base decisions about their research design and data gathering process, on solid empirical advice.

The first research article compared two types of response scales, visual analogue scales (VASs) and Likert-type scales, with regard to non-response. Participants of an eHealth intervention were randomly allocated to answer an extensive questionnaire with either VASs or Likert-type scales as response options to otherwise identical items. A sample of 446 participants with a mean age of 52.4 years (SD=12.1) took part. Results showed lower SDs for items answered via VAS. They also indicated a positive effect of VASs with regard to lowering dropout of participants, OR=.75, p=.04.

The second research article investigated the validity of measurement, again comparing VASs and Likert-type scales. The response scales of three personality scales were varied in a within-design. A sample of 879 participants filled in the Internet-based questionnaire, answering the personality scales twice in a counterbalanced design. Results of Bayesian hierarchical regressions largely indicated measurement equivalence between the two response scale versions, with some evidence for better measurement quality with VASs for one of the personality scale Excitement Seeking, B10=1318.95, ΔR2=.025.

The third research article investigated the validity of objective sensor data in an experience sampling design. The association of subjective well-being with smartphone tilt was investigated in two separate samples implementing different software to gather data. In both samples measurements consisted of cross-sectional questionnaires and a longitudinal period of three weeks, with measurements twice per day. Results provided evidence for the validity of smartphone tilt as an indicator of subjective well-being, t(3392)=-3.9, p<.001. In addition to the analysis of tilt and well-being, potential biases and problems when implementing objective data are discussed, specifically when different software implementations and operating systems are involved.

In conclusion, the PhD thesis offers valuable insights on Internet-based assessment. The VAS’s position as a superior response scale was strengthened.Its advantages over more traditional Likert-type scales, e.g., offering better distributional properties and more valid information, were confirmed and no disadvantages emerged. Smartphone sensor data were shown to provide a way to validate self-report measurement, if potentially important caveats related to differences in data are identified and addressed.