Sarcasm in news

For instance, training was done on Dataset 1 and tested on Dataset 2; the F1-score of the model was Entertainment Wednesday July 25, Abhishek Bachchan was mocked on Twitter as someone not worthy to be in the league of actors previously cast in Anurag Kashyap's films Entertainment Saturday June 30, Uday Chopra merely suggested that trolls be assigned verified accounts in sarcasm laden tweets Khushwant Singh Birth Anniversary: 10 Facts About The Celebrated Author India News Edited by Richa Taneja Friday February 2, Khushwant Singh, the celebrated writer, known for his sharp writings laced with wit, sarcasm and honesty touched chords with the readers.

For those reasons, word embeddings are used as input features.

Sarcasm in news

This would help us in teasing apart the real sarcastic elements. Different training datasets were used to train each model.

sarcasm detection dataset

The proposed model consistently outperforms all the other models. Pathiv's sharp response drew laughs and applause from cricket fans.

See diagram of the CNN-based architecture below To obtain the other features — sentiment Semotion Eand personality P — CNN models are pre-trained and used to extract features from the sarcasm datasets. The noted author offered his views on subjects as diverse as old age and the fear of d Each set of features are learned by separate models, becoming pre-trained models used to extract sarcasm-related features from a dataset.

Pre-trained sentiment, emotion, and personality models are used to capture contextualized information from text.

Experiments Data — Balanced and imbalanced sarcastic tweets datasets were obtained from Ptacek et al. Each set of features are learned by separate models, becoming pre-trained models used to extract sarcasm-related features from a dataset. See visualization of the datasets rendered via PCA below. Pre-trained sentiment, emotion, and personality models are used to capture contextualized information from text. A separate baseline classifier B — consisting of only the CNN model without the incorporation of the other models e. Reposted with permission. Furthermore, since the sole purpose of TheOnion is to publish sarcastic news, we get high-quality labels with much less noise as compared to Twitter datasets. Detection of sarcasm is important in other areas such as affective computing and sentiment analysis because such expressions can flip the polarity of a sentence. He changed his career from a lawyer to a journalist and also got into politics, but he is most remembered for his word craft. This new dataset has following advantages over the existing Twitter datasets: Since news headlines are written by professionals in a formal manner, there are no spelling mistakes and informal usage. For those reasons, word embeddings are used as input features. This reduces the sparsity and also increases the chance of finding pre-trained embeddings. The authors observe that sarcastic expressions are user-specific — some users post more sarcasm than others. TheOnion aims at producing sarcastic versions of current events and we collected all the headlines from News in Brief and News in Photos categories which are sarcastic.

This new dataset has following advantages over the existing Twitter datasets: Since news headlines are written by professionals in a formal manner, there are no spelling mistakes and informal usage.

Detection of sarcasm is important in other areas such as affective computing and sentiment analysis because such expressions can flip the polarity of a sentence.

Rated 9/10 based on 89 review
Download
News Headlines Dataset For Sarcasm Detection