CLApr 27, 2017
Duluth at SemEval-2017 Task 6: Language Models in Humor Detection
arXiv:1704.08390v122 citations
Originality Synthesis-oriented
AI Analysis
This is an incremental approach applying existing methods to a new dataset in computational humor.
The paper tackled humor detection in social media by participating in SemEval-2017 Task 6, using N-gram language models to achieve high rankings in the evaluation.
This paper describes the Duluth system that participated in SemEval-2017 Task 6 #HashtagWars: Learning a Sense of Humor. The system participated in Subtasks A and B using N-gram language models, ranking highly in the task evaluation. This paper discusses the results of our system in the development and evaluation stages and from two post-evaluation runs.