C4.5: programs for machine learning
C4.5: programs for machine learning
Modern Information Retrieval
Reference reconciliation in complex information spaces
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
Why are they excited?: identifying and explaining spikes in blog mood levels
EACL '06 Proceedings of the Eleventh Conference of the European Chapter of the Association for Computational Linguistics: Posters & Demonstrations
Predicting the volume of comments on online news stories
Proceedings of the 18th ACM conference on Information and knowledge management
Automatic summarisation of discussion fora
Natural Language Engineering
Tagging and linking web forum posts
CoNLL '10 Proceedings of the Fourteenth Conference on Computational Natural Language Learning
News comments: exploring, modeling, and online prediction
ECIR'2010 Proceedings of the 32nd European conference on Advances in Information Retrieval
Predicting thread discourse structure over technical web forums
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Multi-objective ranking of comments on web
Proceedings of the 21st international conference on World Wide Web
Care to comment?: recommendations for commenting on news stories
Proceedings of the 21st international conference on World Wide Web
Information Retrieval in the Commentsphere
ACM Transactions on Intelligent Systems and Technology (TIST)
WebTribe: dynamic community analysis from online forums
ICWE'12 Proceedings of the 12th international conference on Web Engineering
Topic-driven reader comments summarization
Proceedings of the 21st ACM international conference on Information and knowledge management
Discovering implicit communities in Web forums through ontologies
Web Intelligence and Agent Systems
Hi-index | 0.00 |
Several on-line daily newspapers offer readers the opportunity to directly comment on articles. In the Netherlands this feature is used quite often and the quality (grammatically and content-wise) is surprisingly high. We develop techniques to collect, store, enrichand analyze these comments. After giving a high-level overview of the Dutch 'commentosphere' we zoom in on extracting the discussion structure found in flat comment threads; people not only comment on the news article, they also heavily comment on other comments, resembling discussion fora. We show how techniques from information retrieval, natural language processing and machine learning can be used to extract the 'reacts-on' relation between comments with high precision and recall.