Descriptors and measurements of verbal violence in tweets GubermanJoshua HemphillLibby 2016 The purpose of this data collection was to test a scale for detecting verbal violence in Tweets. Workers at Mechanical Turk were first asked to complete a qualification test and then invited to code additional Tweets according to our scale. The qualification test involved a detailed explanation of each item of the scale, a walkthrough of a tweet that we had coded according to all 14 scale-items, a practice exercise, and a test.  In the practice exercise, potential coders attempted to code a tweet on their own using our scale.  After submitting their ratings, they were shown our own ratings for the same tweet and explanations for each of our ratings.  The test component consisted of another coding task, in which coders were asked to code another tweet that we had already coded ourselves.  The workers who, on test, with our ratings of that tweet on at least 11 out of the 14 items “passed” the test, earning the qualification that allowed them to participate in future coding tasks.  Variables in the data include the ID of the Tweet (so that you may find it on Twitter; Twitter Terms of Service prohibit us from sharing the Tweets), the ID number we assigned to the coder, the rating that coder provided for each of the 14 items on our scale, the gender and age of the coder, and any comments the coder provided.