The detection and handling of verbal irony in human-computer interaction: a comparison between four chatbots

dc.rights.license	CC-BY-NC-ND
dc.contributor.advisor	Adriaans, F.W.
dc.contributor.author	Weerts, I.J.M.
dc.date.accessioned	2019-05-02T17:00:30Z
dc.date.available	2019-05-02T17:00:30Z
dc.date.issued	2018
dc.identifier.uri	https://studenttheses.uu.nl/handle/20.500.12932/32608
dc.description.abstract	This study investigates what AI-technique works best for detecting and handling verbal irony. The effects of linguistic irony markers have also been taken into consideration. The AI-techniques have been examined through statistical analysis of chatbot replies in ironical human-computer conversations. It has been found that UltraHAL (pattern matching) handles irony significantly better, and that Rose (NLP meaning extraction/ChatScript) handles irony significantly worse, than others.
dc.description.sponsorship	Utrecht University
dc.format.extent	1495514
dc.format.mimetype	application/pdf
dc.language.iso	en
dc.title	The detection and handling of verbal irony in human-computer interaction: a comparison between four chatbots
dc.type.content	Bachelor Thesis
dc.rights.accessrights	Open Access
dc.subject.keywords	Irony, language, linguistics, Artificial Intelligence, Human Computer Interaction, Computer Mediated Communication, pattern matching, Natural Language Processing
dc.subject.courseuu	Kunstmatige Intelligentie