Präsentiert werden Forschungsprojekte und Arbeiten in jeglichem Stadium: Early-Stage-Projekte, Work-in-Progess sowie Publikationen. Anschließend werden die Präsentationen durch die anwesenden Institutsmitglieder und Gasthörer*innen diskutiert und hilfreiche Inputs gegeben.

Termine für das Wintersemester 2020/21 (jeweils 12:30 bis ca. 13:30 Uhr)

• 13.10.2020: Manuel Mayrl (PhD-Student im Doktoratskolleg Political Institutions and Leadership in a Contingent World)
  Press-party parallelism in the digital sphere. Evidence from Austria
  Hörsaal 3 (Sowi)
  

  Abstract
  

  Press-party parallelism in the digital sphere.
  News sharing behavior of political party elites in Austria
  

  The emergence of new media has opened up a new arena for interactions between political and media actors. Especially Twitter has become a channel that on the one hand journalists use to gather information (APA, 2016) and on the other hand politicians use to try to set the media agenda (Seethaler & Melischek, 2019). Thus, finding and sharing news seem to be the driving forces of interaction between politicians and journalists on Twitter (Verweij, 2012).

  Recent studies identified partisan bias in legacy media outlets, even in media markets that are characterized by high journalistic professionalism and independent media (e.g. Haselmayer et al, 2017 for Austria; van der Pas et al, 2017 for Netherlands). This bias also works the other way around, that is, parties are more responsive to media coverage of newspapers their voters read (van der Pas et al., 2017). On Twitter scholars regularly find a similar pattern suggesting that users tend to follow and retweet users that share their political conviction (Jungherr, 2016).

  In this study, I analyze (1) how strongly political party elites use Twitter to spread print media reports and (2), drawing on the concept of press-party parallelism, which print media outlets they share and why they do so. I will draw on three data sources: tweets by political party elites and their official party accounts (N ≈ 27,000), media reports in seven daily newspapers (N ≈ 26,000), and the 2019 AUTNES online panel survey data (n ≈ 3,000). The former two sources cover the period from 05 May 2019 to 29 September 2019, thus including both the European Parliament as well as the Austrian National Parliament election and their campaign periods.

  Methodologically, I use regular expressions operations to identify how often political party elites share print media reports and which media outlets they share. To understand why they share a certain media outlet I test two competing hypotheses. First, based on a demand-side approach, party actors might prefer to share media reports of outlets that are regularly read by their voters. Thus, drawing on the online panel data survey I measure the propensity-to-vote score of each newspaper's regular readership. In the survey, respondents indicated, among others, how often they read daily newspapers as well as how likely they are to ever vote for a given party. A regular reader is operationalized as a survey respondent claiming to read a specific newspaper at least two days a week. Second, based on a supply-side approach, which newspaper a party actor shares might depend on how favorable its coverage towards the party has been. To investigate this hypothesis, I will apply supervised machine learning frame coding (e.g. Bruscher et al, 2014) to assess the overall sentiment of each news article using about 5,000 manually coded print media articles from the 2019 Austrian national election campaign coverage as training data.
  

• 17.11.2020: Andreas Maurer (Univ.-Prof., Jean Monnet Chair for EU Integration Studies)
  How European Institutions Cope with the EU Treaties' Legal Ambiguity - Political and Judicial Mechanisms of Conflict Resolution
  Hörsaal 3 (Sowi)
  

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Technische Anleitung

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