dc.rights.license | CC-BY-NC-ND | |
dc.contributor.advisor | Nouwen, R.W.F. | |
dc.contributor.advisor | Wegmann, A.M. | |
dc.contributor.author | Wolde, M.H. ten | |
dc.date.accessioned | 2021-06-02T18:00:17Z | |
dc.date.available | 2021-06-02T18:00:17Z | |
dc.date.issued | 2021 | |
dc.identifier.uri | https://studenttheses.uu.nl/handle/20.500.12932/39518 | |
dc.description.abstract | Figurative language is seen as the topic that pains Natural Language Processing (NLP) the most. The intention of the figurative language goes beyond the literal meaning of the words. This makes it a real challenge for both humans and computers. Automatic implementations for irony and sarcasm detection are widely researched in English. Satire is a form of figurative language that tries to imitate real news, exposing individuals or organizations to ridicule. Earlier work suggests that an automated assistive tool that detects satire could be the first step in fighting the growing world of fake news. This paper introduces a simple machine learning classifier to automatically detect satire in Dutch headlines, using general features based on textual markers and sentiment. The results of our classifier are promising for further research on automatic figurative language detection in Dutch, but there is some work to do there. Some suggestions for future research are also included | |
dc.description.sponsorship | Utrecht University | |
dc.format.extent | 431526 | |
dc.format.mimetype | application/pdf | |
dc.language.iso | en | |
dc.title | News for the Advanced: A Simple Approach to Automatically Detecting Satire | |
dc.type.content | Bachelor Thesis | |
dc.rights.accessrights | Open Access | |
dc.subject.courseuu | Kunstmatige Intelligentie | |