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These post edits usually involve small-scale sentence edits and our survey of trusted contributors suggests that most of them care much or very much about such small sentence edits. To assist users in making small sentence edits, we develop an edit-assistance tool for identifying minor textual issues in posts and recommending sentence edits for correction. We formulate the sentence editing task as a machine translation problem, in which an original sentence is \"translated\" into an edited sentence. Our tool implements a character-level Recurrent Neural Network (RNN) encoder-decoder model, trained with about 6.8 millions original-edited sentence pairs from Stack Overflow post edits. We evaluate our edit assistance tool using a large-scale archival post edits, a field study of assisting a novice post editor, and a survey of trusted contributors. Our evaluation demonstrates the feasibility of training a deep learning model with post edits by the community and then using the trained model to assist post editing for the community.<\/jats:p>","DOI":"10.1145\/3134667","type":"journal-article","created":{"date-parts":[[2017,12,6]],"date-time":"2017-12-06T21:23:15Z","timestamp":1512595395000},"page":"1-21","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":35,"title":["By the Community &amp; For the Community"],"prefix":"10.1145","volume":"1","author":[{"given":"Chunyang","family":"Chen","sequence":"first","affiliation":[{"name":"Nanyang Technological University, Singapore, Singapore"}]},{"given":"Zhenchang","family":"Xing","sequence":"additional","affiliation":[{"name":"Australian National University, Canberra, Australia"}]},{"given":"Yang","family":"Liu","sequence":"additional","affiliation":[{"name":"Nanyang Technological University, Singapore, Singapore"}]}],"member":"320","published-online":{"date-parts":[[2017,12,6]]},"reference":[{"key":"e_1_2_1_1_1","unstructured":"2017. 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