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Specific applications of automatic summarization include:
* The [[Reddit]] [[Internet bot|bot]] "autotldr",<ref>{{cite web|title=overview for autotldr|url=https://www.reddit.com/user/autotldr|website=reddit|access-date=9 February 2017|language=en}}</ref> created in 2011 summarizes news articles in the comment-section of reddit posts. It was found to be very useful by the reddit community which upvoted its summaries hundreds of thousands of times.<ref>{{cite book|last1=Squire|first1=Megan|author-link = Megan Squire|title=Mastering Data Mining with Python – Find patterns hidden in your data|publisher=Packt Publishing Ltd|isbn=9781785885914|url=https://books.google.com/books?id=_qXWDQAAQBAJ&pg=PA185|access-date=9 February 2017|language=en|date=2016-08-29}}</ref> The name is reference to [[TL;DR]] − [[Internet slang]] for "too long; didn't read".<ref>{{cite web|title=What Is 'TLDR'?|url=https://www.lifewire.com/what-is-tldr-2483633|website=Lifewire|access-date=9 February 2017}}</ref><ref>{{cite web|title=What Does TL;DR Mean? AMA? TIL? Glossary Of Reddit Terms And Abbreviations|url=http://www.ibtimes.com/what-does-tldr-mean-ama-til-glossary-reddit-terms-abbreviations-431704|work=International Business Times|access-date=9 February 2017|date=29 March 2012}}</ref>
* [[Adversarial stylometry]] may make use of summaries, if the detail lost is not major and the summary is sufficiently stylistically different to the input.{{sfn|Potthast|Hagen|Stein|2016|p=11-12}}
==Evaluation==
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==References==
{{Reflist|2}}
== Works cited ==
* {{ cite conference | url = https://ceur-ws.org/Vol-1609/16090716.pdf | title = Author Obfuscation: Attacking the State of the Art in Authorship Verification | last1 = Potthast | first1 = Martin | last2 = Hagen | first2 = Matthias | last3 = Stein | first3 = Benno | conference = Conference and Labs of the Evaluation Forum | year = 2016 }}
== Further reading ==
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