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The Detection of Fake Messages using Machine Learning
Looijenga, M.S. (2018) The Detection of Fake Messages using Machine Learning.
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| Abstract: | This research investigates how fake messages are used on Twitter during the Dutch election of 2012. It researches the performance of 8 supervised Machine Learning classifiers on a Twitter dataset. We provide that the Decision Tree algorithm perform best on the used dataset, with an F-Score of 88%. In total, 613.033 tweets were classified, of which 328.897 were classified as true, and 284.136 tweets were classified as false. Through a qualitative content analysis of false tweets sent during the election, distinctive features and characteristics of false content have been found and grouped into six different categories. |
| Item Type: | Essay (Bachelor) |
| Faculty: | EEMCS: Electrical Engineering, Mathematics and Computer Science |
| Subject: | 54 computer science |
| Programme: | Business & IT BSc (56066) |
| Link to this item: | https://purl.utwente.nl/essays/77385 |
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