Humor Detection

11 papers with code • 1 benchmarks • 3 datasets

Humor detection is the task of identifying comical or amusing elements.

Libraries

Use these libraries to find Humor Detection models and implementations

Most implemented papers

XGBoost: A Scalable Tree Boosting System

dmlc/xgboost 9 Mar 2016

In this paper, we describe a scalable end-to-end tree boosting system called XGBoost, which is used widely by data scientists to achieve state-of-the-art results on many machine learning challenges.

XLNet: Generalized Autoregressive Pretraining for Language Understanding

zihangdai/xlnet NeurIPS 2019

With the capability of modeling bidirectional contexts, denoising autoencoding based pretraining like BERT achieves better performance than pretraining approaches based on autoregressive language modeling.

ColBERT: Using BERT Sentence Embedding for Humor Detection

Moradnejad/ColBERT-Using-BERT-Sentence-Embedding-for-Humor-Detection 27 Apr 2020

In this paper, we propose a novel approach for detecting humor in short texts based on the general linguistic structure of humor.

Humor Detection: A Transformer Gets the Last Laugh

orionw/RedditHumorDetection IJCNLP 2019

These experiments show that this method outperforms all previous work done on these tasks, with an F-measure of 93. 1% for the Puns dataset and 98. 6% on the Short Jokes dataset.

MISA: Modality-Invariant and -Specific Representations for Multimodal Sentiment Analysis

declare-lab/MISA 7 May 2020

In this paper, we aim to learn effective modality representations to aid the process of fusion.

Is This a Joke? Detecting Humor in Spanish Tweets

pln-fing-udelar/pghumor 28 Mar 2017

While humor has been historically studied from a psychological, cognitive and linguistic standpoint, its study from a computational perspective is an area yet to be explored in Computational Linguistics.

A Crowd-Annotated Spanish Corpus for Humor Analysis

pln-fing-udelar/humor WS 2018

Computational Humor involves several tasks, such as humor recognition, humor generation, and humor scoring, for which it is useful to have human-curated data.

Reverse-Engineering Satire, or "Paper on Computational Humor Accepted Despite Making Serious Advances"

epfl-dlab/unfun 10 Jan 2019

Starting from the observation that satirical news headlines tend to resemble serious news headlines, we build and analyze a corpus of satirical headlines paired with nearly identical but serious headlines.

On the Use of Emojis to Train Emotion Classifiers

malayyoub/emojis-to-train-emotion-classifiers 24 Feb 2019

Nonetheless, we experimentally show that training classifiers on cheap, large and possibly erroneous data annotated using this approach leads to more accurate results compared with training the same classifiers on the more expensive, much smaller and error-free manually annotated training data.

DuluthNLP at SemEval-2021 Task 7: Fine-Tuning RoBERTa Model for Humor Detection and Offense Rating

akrahdan/semeval2021 SEMEVAL 2021

This paper presents the DuluthNLP submission to Task 7 of the SemEval 2021 competition on Detecting and Rating Humor and Offense.