README.md

metadata

annotations_creators:
  - Duygu Altinok
language:
  - tr
license:
  - cc-by-sa-4.0
multilinguality:
  - monolingual
size_categories:
  - 100K<n<1M
source_datasets:
  - original
task_categories:
  - text-classification
task_ids:
  - sentiment-classification
pretty_name: SentiTurca (Sentiment Analysis Datasets for Turkish language)
config_names:
  - e-commerce
  - hate
  - movies
tags:
  - sentiment
dataset_info:
  - config_name: hate
    features:
      - name: baslik
        dtype: string
      - name: text
        dtype: string
      - name: label
        dtype:
          class_label:
            names:
              '0': offensive
              '1': hate
              '2': neutral
              '3': civilized
    splits:
      - name: train
        num_bytes: 47357639
        num_examples: 42175
      - name: validation
        num_bytes: 5400927
        num_examples: 5000
      - name: test
        num_bytes: 5323545
        num_examples: 5000
    download_size: 58918801
  - config_name: movies
    features:
      - name: text
        dtype: string
      - name: label
        dtype:
          class_label:
            names:
              '0': negative
              '1': positive
    splits:
      - name: train
        num_bytes: 46979645
        num_examples: 60411
      - name: validation
        num_bytes: 733500
        num_examples: 8905
      - name: test
        num_bytes: 742661
        num_examples: 8934
    download_size: 58918801
  - config_name: e-commerce
    features:
      - name: text
        dtype: string
      - name: label
        dtype:
          class_label:
            names:
              '0': 1_star
              '1': 2_star
              '2': 3_star
              '3': 4_star
              '4': 5_star
    splits:
      - name: train
        num_bytes: 12844466
        num_examples: 73920
      - name: validation
        num_bytes: 4811620
        num_examples: 15000
      - name: test
        num_bytes: 5260694
        num_examples: 15000
configs:
  - config_name: movies
    data_files:
      - split: train
        path: movies/train-*
      - split: validation
        path: movies/validation-*
      - split: test
        path: movies/test-*
  - config_name: e-commerce
    data_files:
      - split: train
        path: e-commerce/train*
      - split: validation
        path: e-commerce/valid*
      - split: test
        path: e-commerce/test*
  - config_name: hate
    data_files:
      - split: train
        path: hate/train-*
      - split: validation
        path: hate/validation-*
      - split: test
        path: hate/test-*

SentiTurca - A Sentiment Analysis Benchmark for Turkish

Dataset Card for SentiTurca

SentiTurca is a sentiment analysis benchmarking dataset including movie reviews, hate speech and e-commerce reviews classification.

Datasets

e-commerce: The e-commerce reviews are scraped from e-commerce websites Trendyol.com and Hepsiburada.com, including review for many product types such as cloths, toys, books, electronics and more.
E-commerce reviews has their stand alone HF repo as well.

movies The movie reviews are scraped from two movie review websites, Sinefil.com and Beyazperde.com. Here, we used 2 labels but for a total challenge of 10 label classification can be found under this dataset's stand alone HF repo. This dataset is also a part of TrGLUE benchmark under the task name sst2.

hate This dataset is the Turkish Hate Map, scraped from Eksisozluk.com and including 4 labels: offense, hate, neutral and civilized.

Dataset statistics

Here are the dataset sizes and number of labels:

Subset	size	num labels
e-commerce	103K	5
movies	78K	2
hate	52K	4

Benchmarking

We benchmarked BERTurk on all of our datasets. All benchmarking scripts can be found under the dedicated SentiTurca Github repo.

Subset	metrics	success
movies	Matthews corr.	0.67
e-commerce	acc./F1	0.66/0.64
hate	acc./F1	0.61/0.58

As one sees, hate dataset is quite challenging. For a full critique of the benchmark please visit our research paper.

Citation

Coming soon!