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» Linguistic Redundancy in Twitter
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NAACL
2010
14 years 10 months ago
Unsupervised Modeling of Twitter Conversations
We propose the first unsupervised approach to the problem of modeling dialogue acts in an open domain. Trained on a corpus of noisy Twitter conversations, our method discovers dia...
Alan Ritter, Colin Cherry, Bill Dolan
81
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COLING
2010
14 years 7 months ago
An Empirical Study on Learning to Rank of Tweets
Twitter, as one of the most popular micro-blogging services, provides large quantities of fresh information including real-time news, comments, conversation, pointless babble and ...
Yajuan Duan, Long Jiang, Tao Qin, Ming Zhou, Heung...
108
Voted
COLING
2010
14 years 7 months ago
Robust Sentiment Detection on Twitter from Biased and Noisy Data
In this paper, we propose an approach to automatically detect sentiments on Twitter messages (tweets) that explores some characteristics of how tweets are written and meta-informa...
Luciano Barbosa, Junlan Feng
99
Voted
ACL
2012
13 years 3 months ago
Extracting and modeling durations for habits and events from Twitter
We seek to automatically estimate typical durations for events and habits described in Twitter tweets. A corpus of more than 14 million tweets containing temporal duration informa...
Jennifer Williams, Graham Katz
68
Voted
COLING
2010
14 years 7 months ago
Collective Semantic Role Labeling on Open News Corpus by Leveraging Redundancy
Xiaohua Liu, Kuan Li, Bo Han, Ming Zhou, Long Jian...