# Context This dataset contains a network of 100k users, out of which ~5k were annotated as hateful or not. For each user, several content-related, network-related and activity related features were provided. Check [this repo](https://github.com/manoelhortaribeiro/HatefulUsersTwitter) for analysis and a straightforward classification approach and [this repo](https://github.com/manoelhortaribeiro/graphsage_hateful_users) where we employed GraphSage, a network embedding method; *Hint*: Try to use not only the content associated with each user but also Twitter's network structure. # Content - `users_anon_neighborhood.csv` file with several features for each user as well as the avg for some features for their 1-neighborhood (ppl they tweeted). Notice that `c_` are attributes calculated for the 1-neighborhood of a user in the retweet network (averaged out). - `users_clean.graphml` networkx compatible file with retweet network. User id's correspond to those in `users_anon_neighborhood.csv`! If you're keen on the original tweets, contact me :). ## For reproducibility purposes This are the files used by GraphSage [here](https://github.com/manoelhortaribeiro/graphsage_hateful_users). They come in a special format :); I've added "_" - `_users_(hate|suspended)_(glove|all).content` files with the feature vector for each user and their classes, the ones with `hate` label users as either `hateful`, `normal` or `other`, whereas the ones with `suspended` label users as either `suspended` or active. The ones with `glove` have only the glove vectors as features, the ones with `all` have other attributes related to users activity and network centrality. This is only for the GraphSage algorithm. - `_user.edges` file with all the (directed) edges in the retweet graph. # Attributes description hate :("hateful"|"normal"|"other") if user was annotated as hateful, normal, or not annotated. (is_50|is_50_2) :bool whether user was deleted up to 12/12/17 or 14/01/18. (is_63|is_63_2) :bool whether user was suspended up to 12/12/17 or 14/01/18. (hate|normal)_neigh :bool is the user on the neighborhood of a (hateful|normal) user? [c_] (statuses|follower|followees|favorites)_count :int number of (tweets|follower|followees|favorites) a user has. [c_] listed_count:int number of lists a user is in. [c_] (betweenness|eigenvector|in_degree|outdegree) :float centrality measurements for each user in the retweet graph. [c_] *_empath :float occurrences of empath categories in the users latest 200 tweets. [c_] *_glove :float glove vector calculated for users latest 200 tweets. [c_] (sentiment|subjectivity) :float average sentiment and subjectivity of users tweets. [c_] (time_diff|time_diff_median) :float average and median time difference between tweets. [c_] (tweet|retweet|quote) number :float percentage of direct tweets, retweets and quotes of an user. [c_] (number urls|number hashtags|baddies|mentions) :float number of bad words|mentions|urls|hashtags per tweet in average. [c_] status length :float average status length. hashtags :string all hashtags employed by the user separated by spaces.