README.md · eduagarcia/tweetsentbr_fewshot at c1a3d7c0de48593e5a734598efd397740bcae77f

metadata

dataset_info:
  features:
    - name: id
      dtype: int64
    - name: sentence
      dtype: string
    - name: label
      dtype: string
  splits:
    - name: train
      num_bytes: 6830
      num_examples: 75
    - name: test
      num_bytes: 178392
      num_examples: 2010
  download_size: 111622
  dataset_size: 185222
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: test
        path: data/test-*
task_categories:
  - text-classification
language:
  - pt
size_categories:
  - 1K<n<10K

tweetSentBR (Few-shot)

This dataset is a subset of the tweetSentBR, it contains only 75 samples from the training set and all 2.000+ instances of the test set.
This is meant for evaluating language models in a few-shot setting on the 🚀 Open Portuguese LLM Leaderboard with the portuguese fork of the Eleuther AI Language Model Evaluation Harness

For the complete dataset with 15.000+ annotated tweets go to https://bitbucket.org/HBrum/tweetsentbr or contact the paper authors: http://www.lrec-conf.org/proceedings/lrec2018/summaries/389.html

Description

TweetSentBR is a corpus of Tweets in Brazilian Portuguese. It was labeled by several annotators following steps stablished on the literature for improving reliability on the task of Sentiment Analysis. Each Tweet was annotated in one of the three following classes:

Positive - tweets where a user meant a positive reaction or evaluation about the main topic on the post;
Negative - tweets where a user meant a negative reaction or evaluation about the main topic on the post;
Neutral - tweets not belonging to any of the last classes, usually not making a point, out of topic, irrelevant, confusing or containing only objective data.

Citation

@InProceedings{BRUM18.389,
  author = {Henrico Brum and Maria das Gra\c{c}as Volpe Nunes},
  title = "{Building a Sentiment Corpus of Tweets in Brazilian Portuguese}",
  booktitle = {Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)},
  year = {2018},
  month = {May 7-12, 2018},
  address = {Miyazaki, Japan},
  editor = {Nicoletta Calzolari (Conference chair) and Khalid Choukri and Christopher Cieri and Thierry Declerck and Sara Goggi and Koiti Hasida and Hitoshi Isahara and Bente Maegaard and Joseph Mariani and HÚlŔne Mazo and Asuncion Moreno and Jan Odijk and Stelios Piperidis and Takenobu Tokunaga},
  publisher = {European Language Resources Association (ELRA)},
  isbn = {979-10-95546-00-9},
  language = {english}
}

Dataset Description

Homepage:
Repository: https://bitbucket.org/HBrum/tweetsentbr
Paper: Building a Sentiment Corpus of Tweets in Brazilian Portuguese