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Detecting controversy on the web
Abstract A useful feature to facilitate critical liA useful feature to facilitate critical literacy would alert users when they are reading a controversial web page. This requires solving a binary classification problem: does a given web page discuss a controversial topic? We explore the feasibility of solving the problem by treating it as supervised k-nearest-neighbor classification. Our approach (1) maps a webpage to a set of neighboring Wikipedia articles which were labeled on a controversiality metric; (2) coalesces those labels into an estimate of the webpage's controversiality; and finally (3) converts the estimate to a binary value using a threshold. We demonstrate the applicability of our approach by validating it on a set of webpages drawn from seed queries. We show absolute gains of 22% in F 0.5 on our test set over a sentiment-based approach, highlighting that detecting controversy is more complex than simply detecting opinions. Copyright is held by the owner/author(s). Copyright is held by the owner/author(s).
Abstractsub A useful feature to facilitate critical liA useful feature to facilitate critical literacy would alert users when they are reading a controversial web page. This requires solving a binary classification problem: does a given web page discuss a controversial topic? We explore the feasibility of solving the problem by treating it as supervised k-nearest-neighbor classification. Our approach (1) maps a webpage to a set of neighboring Wikipedia articles which were labeled on a controversiality metric; (2) coalesces those labels into an estimate of the webpage's controversiality; and finally (3) converts the estimate to a binary value using a threshold. We demonstrate the applicability of our approach by validating it on a set of webpages drawn from seed queries. We show absolute gains of 22% in F 0.5 on our test set over a sentiment-based approach, highlighting that detecting controversy is more complex than simply detecting opinions. Copyright is held by the owner/author(s). Copyright is held by the owner/author(s).
Bibtextype inproceedings  +
Doi 10.1145/2505515.2507877  +
Has author Dori-Hacohen S. + , Allan J. +
Has extra keyword Absolute gain + , Binary classification problems + , Binary values + , Controversial topic + , Critical literacy + , K-nearest neighbors + , Sentiment analysis + , Wikipedia articles + , Knowledge management + , Websites +
Has keyword Controversy detection + , Critical literacy + , Sentiment analysis +
Isbn 9781450322638  +
Language English +
Number of citations by publication 0  +
Number of references by publication 0  +
Pages 1845–1848  +
Published in International Conference on Information and Knowledge Management, Proceedings +
Title Detecting controversy on the web +
Type conference paper  +
Year 2013 +
Creation dateThis property is a special property in this wiki. 7 November 2014 17:51:57  +
Categories Publications without license parameter  + , Publications without remote mirror parameter  + , Publications without archive mirror parameter  + , Publications without paywall mirror parameter  + , Conference papers  + , Publications without references parameter  + , Publications  +
Modification dateThis property is a special property in this wiki. 7 November 2014 17:51:57  +
DateThis property is a special property in this wiki. 2013  +
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