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In recent years, the number of texts has grown rapidly. For example, most reviewbased portals, like Yelp or Amazon, contain thousands of user-generated reviews. It is impossible for any human reader to process even the most relevant of these documents. The most promising tool to solve this task is a text summarization. Most existing approaches, however, work on small, homogeneous, English datasets, and do not account to multi-linguality, opinion shift, and domain effects. In this paper, wedoi:10.18653/v1/p18-3001 dblp:conf/acl/Pecar18 fatcat:5d3p4w6gvvfixdvp2jpcq6l4ia