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In this article, we propose a comprehensive sentiment analysis system for Turkish. We cover different levels of sentiment analysis such as aspect, sentence, and document levels as well as some linguistic issues such as conjunction and intensification in Turkish sentiment analysis. Our system is evaluated on Turkish movie reviews and the obtained accuracies range from sixty per cent to seventy-nine per cent in ternary and binary classification tasks at different levels of analysis.<\/jats:p>","DOI":"10.1017\/s1351324916000309","type":"journal-article","created":{"date-parts":[[2016,10,21]],"date-time":"2016-10-21T11:59:35Z","timestamp":1477051175000},"page":"535-559","source":"Crossref","is-referenced-by-count":27,"title":["Sentiment analysis in Turkish at different granularity levels"],"prefix":"10.1017","volume":"23","author":[{"given":"RAHIM","family":"DEHKHARGHANI","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"BERRIN","family":"YANIKOGLU","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"YUCEL","family":"SAYGIN","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"KEMAL","family":"OFLAZER","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"56","published-online":{"date-parts":[[2016,10,21]]},"reference":[{"key":"S1351324916000309_ref014","doi-asserted-by":"publisher","DOI":"10.1111\/j.0824-7935.2004.t01-1-00228.x"},{"key":"S1351324916000309_ref033","unstructured":"Seslis\u00f6zl\u00fck Group. 2014. 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