| Creators: |
Janze, Christian and Risius, Marten |
| Title: |
Automatic Detection of Fake News on Social Media Platforms |
| Item Type: |
Conference or Workshop Item |
| Event Title: |
(Proceedings of the) 21st Pacific Asia Conference on Information Systems (PACIS) |
| Event Location: |
Langkawi Island, Malaysia |
| Event Dates: |
July, 16-20, 2017 |
| Projects: |
IDI |
| Additional Information: |
Winner of the Best Conference Paper Award |
| Date: |
2017 |
| Divisions: |
Informationsmanagement |
| Abstract (ENG): |
This study investigates how fake news shared on social media platforms can be automatically identified. Drawing on the Elaboration Likelihood Model and previous studies on information quality, we develop and test an explorative research model on Facebook news posts during the U.S. presidential election 2016. The study examines how cognitive, visual, affective and behavioral cues of the news posts as well as of the addressed user community can be used by machine learning classifiers to identify fake news fully automatically. The best performing configurations achieve a stratified 10-fold cross validated predictive accuracy of more than 80%, and a recall rate (share of correctly identified fake news) of nearly 90% on a balanced data sample solely based on data directly available on Facebook. Platform operators and users can draw on the results to identify fake news on social media platforms - either automatically or heuristically. |
| Forthcoming: |
No |
| Language: |
English |
| Citation: |
Janze, Christian and Risius, Marten
(2017)
Automatic Detection of Fake News on Social Media Platforms.
In: (Proceedings of the) 21st Pacific Asia Conference on Information Systems (PACIS), July, 16-20, 2017, Langkawi Island, Malaysia.
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