1. Description: The Facebook Movies dataset contains a list of movies and the number of Facebook likes for each movie. To generate the dataset we first selected 10,000 movies from DBpedia, which were then linked to the corresponding Facebook page. To get high quality links, we used exact matching on the movie's name and the movie's director. The final dataset contains 1,600 movies, which was created by first ordering the list of movies based on the number of Facebook likes, and then selecting the top 800 movies and the bottom 800 movies. To retrieve the number of Facebook likes we used the Facebook Graph API (https://developers.facebook.com/docs/graph-api). We use the dataset both for regression as well as for classification, discretizing the target variable into ``good'' and ``bad'', using equal frequency binning. 2.ML taks: classificaiton and regression 3. Number of instances: 1600 4. Original source: Facebook 5. Linked to: DBpedia 6. Target variables -score (Regression): discretized to "label" (classification) by the rule: bad<5000;good