The detection and handling of verbal irony in human-computer interaction: a comparison between four chatbots
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Bachelor Thesis
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CC-BY-NC-ND
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.
Keywords
Irony, language, linguistics, Artificial Intelligence, Human Computer Interaction, Computer Mediated Communication, pattern matching, Natural Language Processing