Abstract
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 effect of negative words on news consumption using a massive online dataset of viral news stories. Specifically, we conducted preliminary analyses using a large-scale, series of randomized controlled trials in the field (N = 22,743). Our final dataset will comprise ∼105,000 different variations of news stories from Upworthy.com–one of the fastest growing websites of all time–that generated ∼8 million clicks across more than 530 million overall impressions. As such, this dataset allows a unique opportunity to test the causal impact of negative and emotional language on consumption with millions of news readers. An analysis with preliminary data reveals that negative words in news increase consumption rates. Our results contribute to a better understanding of why users engage with online media.
Dokumententyp: | Zeitschriftenartikel |
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Keywords: | Artificial Intelligence; AI, Künstliche Intelligenz; KI |
Fakultät: | Betriebswirtschaft > Institute of Artificial Intelligence (AI) in Management |
Themengebiete: | 000 Informatik, Informationswissenschaft, allgemeine Werke > 000 Informatik, Wissen, Systeme |
URN: | urn:nbn:de:bvb:19-epub-94951-0 |
Sprache: | Englisch |
Dokumenten ID: | 94951 |
Datum der Veröffentlichung auf Open Access LMU: | 08. Mrz. 2023, 07:48 |
Letzte Änderungen: | 04. Jan. 2024, 11:22 |