Difference between revisions of "Popescu and Pennacchiotti, CIKM 10"
From Cohen Courses
Jump to navigationJump to searchm (Created page with 'This [[Category::Paper]] is relevant to our project on detecting controversial events in Twitter. == Citation == Ana-Maria Popescu and Marco Pennacchiotti. Detecting controvers…') |
m |
||
Line 1: | Line 1: | ||
This [[Category::Paper]] is relevant to our project on detecting controversial events in Twitter. | This [[Category::Paper]] is relevant to our project on detecting controversial events in Twitter. | ||
+ | |||
+ | = Detecting controversial events from Twitter = | ||
== Citation == | == Citation == | ||
Line 10: | Line 12: | ||
== Summary == | == Summary == | ||
+ | |||
+ | This paper addresses the task of identifying controversial events using Twitter as a starting point. | ||
== Evaluation == | == Evaluation == | ||
Line 22: | Line 26: | ||
* [[RelatedPaper::Yang et al, SIGIR 98|A study on retrospective and online event detection. Yang et al, SIGIR 98]] This paper addresses the problems of detecting events in news stories. | * [[RelatedPaper::Yang et al, SIGIR 98|A study on retrospective and online event detection. Yang et al, SIGIR 98]] This paper addresses the problems of detecting events in news stories. | ||
* [[RelatedPaper::Zhao et al, AAAI 07|Temporal and information flow based event detection from social text streams. Zhao et al, AAAI 07]] This paper addresses the problems of detecting events in news stories. | * [[RelatedPaper::Zhao et al, AAAI 07|Temporal and information flow based event detection from social text streams. Zhao et al, AAAI 07]] This paper addresses the problems of detecting events in news stories. | ||
− | * [[RelatedPaper::Automatic_Detection_and_Classification_of_Social_Events|Automatic Detection and Classification of Social Events]] This paper aims at detecting and classifying social events using Tree kernels. | + | * [[RelatedPaper::Automatic_Detection_and_Classification_of_Social_Events|Automatic Detection and Classification of Social Events. Agarwal and Rambow, ACL 10]] This paper aims at detecting and classifying social events using Tree kernels. |
+ | * [[RelatedPaper::Castillo_2011|Information credibility on twitter. Castillo et al, WWW 11]] The authors develop a general approach to change-point detection that generalize across wide range of application. | ||
== Study plan == | == Study plan == | ||
* Article: Adaptive time series model [http://www.siam.org/proceedings/datamining/2007/dm07_059Lemire.pdf] | * Article: Adaptive time series model [http://www.siam.org/proceedings/datamining/2007/dm07_059Lemire.pdf] | ||
* Graph cut based clustering [http://www.cs.berkeley.edu/~malik/papers/SM-ncut.pdf] | * Graph cut based clustering [http://www.cs.berkeley.edu/~malik/papers/SM-ncut.pdf] |
Revision as of 22:35, 30 September 2012
This Paper is relevant to our project on detecting controversial events in Twitter.
Contents
Detecting controversial events from Twitter
Citation
Ana-Maria Popescu and Marco Pennacchiotti. Detecting controversial events from Twitter. In Proceedings of the 19th ACM international conference on Information and knowledge management, CIKM ’10, pages 1873–1876, New York, NY, USA, 2010. ACM.
Online version
Detecting controversial events from Twitter
Summary
This paper addresses the task of identifying controversial events using Twitter as a starting point.
Evaluation
Discussion
Related papers
There has been a lot of work on event detection.
- A Statistical Model for Popular Events Tracking in Social Communities. Lin et al, KDD 2011 This paper address a method to observe and track the popular events or topics that evolve over time in the communities.
- A study on retrospective and online event detection. Yang et al, SIGIR 98 This paper addresses the problems of detecting events in news stories.
- Temporal and information flow based event detection from social text streams. Zhao et al, AAAI 07 This paper addresses the problems of detecting events in news stories.
- Automatic Detection and Classification of Social Events. Agarwal and Rambow, ACL 10 This paper aims at detecting and classifying social events using Tree kernels.
- Information credibility on twitter. Castillo et al, WWW 11 The authors develop a general approach to change-point detection that generalize across wide range of application.