University of Twente Student Theses
Sentiment as a ground truth stance indicator against fake news
Steegh, E.G.A.J. (2021) Sentiment as a ground truth stance indicator against fake news.
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| Abstract: | This report investigates a novel ground truth approach to fake news detection, focusing on sentiment detection to interpret the author’s stance. A three-pronged model was built combining an LDA for topic detection, VADER to create sentiment sequence, a stacked LSTM to interpret those sentiment sequences and a statistical description of the sequences. The model interpreted the popular ISOT fake news dataset to build a knowledge base and achieved an 80% instance classification accuracy on the dataset using J48, finding value in sentiment analysis as a tool for fake news detection. |
| Item Type: | Essay (Bachelor) |
| Faculty: | EEMCS: Electrical Engineering, Mathematics and Computer Science |
| Subject: | 17 linguistics and theory of literature, 54 computer science |
| Programme: | Creative Technology BSc (50447) |
| Link to this item: | https://purl.utwente.nl/essays/86058 |
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