@inproceedings{Thelwall2013,
   author = "Thelwall, Mike and Buckley, Kevan and Paltoglou, George and Skowron, Marcin and Garcia, David and Gobron, Stephane and Ahn, Junghyun and Kappas, Arvid and Kuster, Dennis and Janusz, A",
   title = "Damping sentiment analysis in online communication: Discussions, monologs and dialogs",
   abstract = "Sentiment analysis programs are now sometimes used to detect pat - terns of sentiment use over time in online communication and to help automated systems interact better with users. Nevertheless, it seems that no previouspublished study has assessed whether the position of individual texts within ongoing communication can be exploited to help detect their sentiments. This article assesses apparent sentiment anomalies in on - going communication textsassigned significantly different sentiment strength to the average of previoustexts to see whether their classification can be improved. The results suggestthat a damping procedure to reduce sudden large changes in sentiment can improve classification accuracy but that the optimal procedure will depend on thetype of texts processed.",
   mendeleytags = "PRJ_CYBEREM,SG-Publication,TOP_COLEM,sentiment analysis",
   pages = "1-- 12",
   year = "2013",
   keywords = "PRJ_CYBEREM,SG-Publication,TOP_COLEM,sentiment analysis",
   date_added = "2013-02-18 19:06:44.771538",
   booktitle = "Proceedings of the 25th International Conference on Computational Linguistics (COLING)"
}