Professur für Data Science & Digitalisierung
- Leitung der Professur
-
Prof. Dr. Nicolas Pröllochs
Licher Straße 62
D-35394 Gießen
nicolas.proellochs@wi.jlug.de
Persönliche Website: https://www.nproellochs.com
- News
-
BWL XI: Paper in Nature Human BehaviourA new research paper examining the causal impact of negativity on news consumption has been accepted for publication in Nature Human Behaviour (IF: 24.25). The results of the study demonstrate a robust and causal negativity bias in news consumption from a massive dataset from the field.
-
BWL XI: Paper in PNAS NexusA new research paper studying the antecedents of hate speech on social media has been accepted for publication in PNAS Nexus. Based on three large-scale datasets across three domains (politics, news media, and activism), the study demonstrates that moralized language in social media posts fosters the proliferation of hate speech.
-
BWL XI: Text Mining Course in Winter Semester 22/23In winter semester 22/23, we offer the course "Text Mining" for master's students. The number of participants is limited to a maximum number of 24 students. The deadline for applications is October 7, 2022.
-
BWL XI: Two papers accepted at ICWSMTwo new research papers have been accepted for publication in the proceedings of the International Conference on Web and Social Media (ICWSM). The papers analyze user behavior on the alt-right social media platform Parler.
- Featured Research: Moralized language predicts hate speech on social media
-
This study provides large-scale observational evidence that moralized language fosters the proliferation of hate speech on social media. Specifically, we analyzed three datasets from Twitter covering three domains (politics, news media, and activism) and found that the presence of moralized language in source posts was a robust and meaningful predictor of hate speech in the corresponding replies. These findings offer new insights into the mechanisms underlying the proliferation of hate speech on social media and may help to inform educational applications, counterspeech strategies, and automated methods for hate speech detection.
Paper at PNAS Nexus (open access)