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Professur für Data Science & Digitalisierung

News
BWL XI: Study on Deepfakes at IC2S2
Our study "Characterizing Deepfakes on X" has been accepted for presentation at the International Conference on Computational Social Science (IC2S2 '25).
BWL XI: Media Coverage in TIME Magazine & The Atlantic
Our research on community-based fact-checking has been featured in TIME Magazine and The Atlantic.
BWL XI: Interview im 1E9 Magazin
Nutzen oder schaden die sozialen Medien der Demokratie? Darüber und über weitere Themen hat Prof. Nicolas Pröllochs in einem Interview mit dem 1E9 Magazin gesprochen.
BWL XI: Podcast im DLF
Berichten Medien zu negativ? In der neuen Folge des Deutschlandfunk-Podcasts „Nach Redaktionsschluss“ diskutiert Prof. Nicolas Pröllochs über seine Forschung zu Negativität im Nachrichtenkonsum – und darüber, warum gerade negative Schlagzeilen oft besonders viel Aufmerksamkeit bekommen.
BWL XI: DFG Grant for Research on Community-Based Fact-Checking
The German Research Foundation (DFG) has awarded a new research grant to Prof. Dr. Nicolas Pröllochs. The funding will support our research on community-based fact-checking on social media.
BWL XI: Paper accepted in PNAS Nexus
A new research paper has been accepted for publication in PNAS Nexus. In our study, we estimate the link between online political advertising and election outcomes during the 2021 German federal election.
BWL XI: New Master's Course -- Applied AI (SS 25)
In the summer semester of 2025, we offer a new course "Applied AI" for master's students. The number of participants is limited to a maximum number of 24 students. The deadline for applications is April 14, 2025.
BWL XI: Paper accepted at CHI
A new research paper has been accepted for publication in the Proceedings of the ACM Conference on Human Factors in Computing Systems (CHI). CHI is the leading conference in human–computer interaction with a low acceptance rate (CORE Ranking A*).
BWL XI: Paper in Nature Reviews Psychology
A new article has been accepted for publication in Nature Reviews Psychology (IF: 16.8). Together with an interdisciplinary team of domain experts, we describe how natural language processing (NLP) can be used to analyse text data in behavioural science.
BWL XI: Paper accepted at ICWSM
A new research paper has been accepted for publication in the Proceedings of the International Conference on Web and Social Media (ICWSM). ICWSM is a premier conference in data science with a low acceptance rate (CORE Ranking A).
BWL XI: Research Featured in The Washington Post
Our research studying community-based fact-checking on X/Twitter has been featured in The Washington Post.
BWL XI: Wiss. MA / Doktorand/in gesucht
An der Professur für Data Science und Digitalisierung (BWL XI) ist zum nächstmögliche Zeitpunkt eine Stelle als Wiss. MA / Doktorand/in zu besetzen. Nähere Informationen in der Stellenanzeige. Wir freuen uns auf Ihre Bewerbung!
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Leitung der Professur

Featured Research: Community Notes Increase Trust in Fact-Checking on Social Media

Social media providers have been called upon to develop effective countermeasures to combat the spread of misinformation on their platforms. However, a large proportion of users distrust professional fact-checkers and the stance on fact-checking is increasingly becoming a partisan issue. In this study, we demonstrate that community-based fact-checking systems (e.g. X’s Community Notes) that focus on providing fact-checking context have the potential to mitigate trust issues that are common in traditional approaches to fact-checking on social media. Fostering trust in fact-checking is vitally important, especially as we face emerging challenges due to AI-generated misinformation.

Featured Research: Negativity Drives Online News Consumption

Online media is important for society in informing and shaping opinions, hence raising the question of what drives online news consumption. Here, we analyze the causal effect of negative and emotional words on news consumption using a large online dataset of viral news stories. Specifically, we conducted our analyses using a series of randomized controlled trials (N = 22,743). Our dataset comprises ∼105,000 different variations of news stories from Upworthy.com that generated ∼5.7 million clicks across more than 370 million overall impressions. Although positive words were slightly more prevalent than negative words, we found that negative words in news headlines increased consumption rates (and positive words decreased consumption rates). For a headline of average length, each additional negative word increased the click-through rate by 2.3% Our results contribute to a better understanding of why users engage with online media.