Im Rahmen der Zwischenevaluation seines laufenden Tenure-Track-Verfahrens lädt Jun.-Prof. Dr. Raoul Kübler vom Marketing Center Münster am Donnerstag, den 24. März, ab 9:00 Uhr zu einer hochschulöffentlichen Lehrprobe mit anschließendem Forschungsvortrag ein. Die beiden Veranstaltungsteile dauern jeweils 20 Minuten. Der Titel der Lehrprobe lautet: “Introduction to Data Science – Session: User Generated Content and Text Mining” (Bachelor-Vorlesung). Der Fachvortrag trägt den Titel “How Social Media Drove the 2016 and 2020 U.S. Presidential Elections”.

Alle Interessierten sind herzlich willkommen! Die Zugangsdaten zum Zoom-Meeting stellt Ihnen Frau Moch (n.moch@uni-muenster.de) auf Anfrage gerne zur Verfügung.

Abstract Forschungsvortrag:

How did social media interactions versus the candidates’ own actions drive the 2016 and 2020 election outcome? Were candidates misled if they focused on prediction markets, traditional market research versus the newer probabilistic polls? Based on the dynamic political will formation framework, the authors address these questions with a daily data set combining donations, polls and advertising with social media interactions on Twitter, Facebook, and Instagram. Persistence modeling reveals a very different impact on traditional versus the probabilistic polls, showing the danger of relying on 1 predictive metric. Candidates largely control their own fate, but the impact of their paid actions differs by channel, topic and how they resonate in social media. Disinformation about the candidates hurts their chances on some topics, while boosting them on others.  Applying the learnings from the 2016 election, the authors predict the 2020 election and draw insights to advise where, when and how to drive the political conversation.