Predicting the quality of user contributions via LSTMs

  title={Predicting the quality of user contributions via LSTMs},
  author={Rakshit Agrawal and Luca de Alfaro},
In many collaborative systems it is useful to automatically estimate the quality of new contributions; the estimates can be used for instance to flag contributions for review. To predict the quality of a contribution by a user, it is useful to take into account both the characteristics of the revision itself, and the past history of contributions by that user. In several approaches, the user's history is first summarized into a number of features, such as number of contributions, user… CONTINUE READING
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