ajgt_twitter_ar
Arabic Jordanian General Tweets (AJGT) Corpus consisted of 1,800 tweets annotated as positive and negative. Modern Standard Arabic (MSA) or Jordanian dialect.
Datasets
9ar_res_reviews
Dataset of 8364 restaurant reviews scrapped from qaym.com in Arabic for sentiment analysis
emotone_ar
Dataset of 10065 tweets in Arabic for Emotion detection in Arabic text
interpress_news_category_tr
It is a Turkish news data set consisting of 273601 news in 17 categories, compiled from print media and news websites between 2010 and 2017 by the Interpress (https://www.interpress.com/) media monitoring company.
labr
This dataset contains over 63,000 book reviews in Arabic.It is the largest sentiment analysis dataset for Arabic to-date.The book reviews were harvested from the website Goodreads during the month or March 2013.Each book review comes with the goodreads review id, the user id, the book id, the rating (1 to 5) and the text of the review.
offenseval2020_tr
OffensEval-TR 2020 is a Turkish offensive language corpus. The corpus consist of randomly sampled tweets and annotated in a similar way to OffensEval and GermEval.
ttc4900
The data set is taken from kemik group http://www.kemik.yildiz.edu.tr/ The data are pre-processed for the text categorization, collocations are found, character set is corrected, and so forth. We named TTC4900 by mimicking the name convention of TTC 3600 dataset shared by the study http://journals.sagepub.com/doi/abs/10.1177/0165551515620551
turkish_movie_sentiment
This data set is a dataset from kaggle consisting of Turkish movie reviews and scored between 0-5.
turkish_product_reviews
Turkish Product Reviews. This repository contains 235.165 product reviews collected online. There are 220.284 positive, 14881 negative reviews.