1. Badges: Badges labeled with a "+" or "-" as a function of a person's name
2. BuddyMove Data Set: User interest information extracted from user reviews published in holidayiq.com about various types of point of interests in South India
3. Drug Review Dataset (Druglib.com): The dataset provides patient reviews on specific drugs along with related conditions. Reviews and ratings are grouped into reports on the three aspects benefits, side effects and overall comment.
4. Drug Review Dataset (Drugs.com): The dataset provides patient reviews on specific drugs along with related conditions and a 10 star patient rating reflecting overall patient satisfaction.
5. Guitar Chords finger positions: Position of the fingers for 2633 guitar chords in standard tuning (double checked with software)
6. Online Retail II: A real online retail transaction data set of two years.
7. Reuters-21578 Text Categorization Collection: This is a collection of documents that appeared on Reuters newswire in 1987. The documents were assembled and indexed with categories.
8. Roman Urdu Data Set: Roman Urdu (the scripting style for Urdu language) is one of the limited resource languages.A data corpus comprising of more than 20000 records was collected.
9. Russian Corpus of Biographical Texts: Sentence classification (Russian). The corpus contains Wikipedia texts splitted into sentences/ Each sentence has a topic label.
10. Syskill and Webert Web Page Ratings: This database contains HTML source of web pages plus the ratings of a single user on these web pages. Web pages are on four seperate subjects (Bands- recording artists; Goats; Sheep; and BioMedical)
11. Turkish Spam V01: The TurkishSpam data set contains spam and normal emails written in Turkish.
12. Twitter Data set for Arabic Sentiment Analysis: This problem of Sentiment Analysis (SA) has been studied well on the English language but not Arabic one. Two main approaches have been devised: corpus-based and lexicon-based.
13. University of Tehran Question Dataset 2016 (UTQD.2016): Persian questions gathered from a jeopardy game broadcasted on Iranian national television.
14. YouTube Comedy Slam Preference Data: This dataset provides user vote data on which video from a pair of videos is funnier collected on YouTube Comedy Slam. The task is to automatically predict this preference based on video metadata.
15. Youtube cookery channels viewers comments in Hinglish: The datasets are taken from top 2 Indian cooking channel named Nisha Madhulika channel and Kabita’s Kitchen channel.
The data set is in Hinglish Language.
16. YouTube Spam Collection: It is a public set of comments collected for spam research. It has five datasets composed by 1,956 real messages extracted from five videos that were among the 10 most viewed on the collection period.