tweet-classification
tweetclassification-bf-modelcamembert-fr-covid-tweet-sentiment-classificationcamembert-fr-covid-tweet-classificationautonlp-tweets-classification-23044997disaster-tweet-distilbert-classificationCOVID-19-CT-tweets-classificationdistilbert-base-uncased-finetuned-Tweets_IMDB_dataset-finetuned-text_classificationissue_classification_tweets
task1489_sarcasmdetection_tweet_classification
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task1489_sarcasmdetection_tweet_classification
Additional Information
Citation Information
The following paper introduces the corpus in detail. If you use the corpus in published work, please cite it:
@misc{wang2022supernaturalinstructionsgeneralizationdeclarativeinstructions,
title={Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+… See the full description on the dataset page: https://huggingface.co/datasets/Lots-of-LoRAs/task1489_sarcasmdetection_tweet_classification.macedonian-tweet-sentiment-classification
Dataset Card for Macedonian Tweet Sentiment Classification
Dataset Description
Dataset Summary
This is a Macedonian dataset is a collection of tweets for sentiment classification.
Supported Tasks and Leaderboards
text-classification, sentiment-classification: The dataset can be used to train a model for sentiment classification. The model performance is evaluated based on the accuracy of the predicted labels as compared to the given labels in the… See the full description on the dataset page: https://huggingface.co/datasets/isaacchung/macedonian-tweet-sentiment-classification.azerbaijani_tweet_emotion_classificationThis dataset contains 150K (train + test) cleaned tweets in Azerbaijani. Tweets were collected in 2021, and filtered and cleaned by following these steps:
Initial data were collected by using twint library. The tool is currently deprecated, cannot be used with new Twitter.
On top of the already filtered data, I applied an additional filter to select Azerbaijani tweets with using fastText language identification model.
Tweets were classified into 3 emotion categories: {positive: 1, negative:… See the full description on the dataset page: https://huggingface.co/datasets/hajili/azerbaijani_tweet_emotion_classification.covid-tweet-text-classificationcovid-tweet-text-classificationmteb-human-tweet-sentiment-classification
Tweet Sentiment subset
Balanced per class; gold labels from official test.