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The WebGenre Blog: The power of genre applied to digital information. By Marina Santini » Archive

Impact of Sociolinguistics in Opinion Mining Systems

Signed post by Alexander Osherenko, Socioware Development, osherenko@socioware.de Full paper: Considering Impact of Sociolinguistic Findings in Believable Opinion Mining Systems Proceedings of The Fifth International Conference On Cognitive Science. 2012. Kalinigrad, Russia (http://www.informatik.uni-augsburg.de/~osherenk/final_kalinigrad.pdf) Opinions are frequent means of communication in human society and automatic approaches to opinion mining in texts attracted therefore much attention. All in all, most approaches apply data mining techniques and extract lexical features (words) as reliable means of classi cation. Noteworthy that although the interest in opinion mining is huge, there are only few explorations on words extracted in opinion mining. This study considers this drawback and elaborates on a sociolinguistic explanation. We hypothesize: an opinion mining system should be trained for classifying opinions in texts of the same language style. Hence, this contribution focuses on the following questions: 1) do sociolinguistic … Read entire article »

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White Paper: Automatic Genre Identification – Testing with Noise

Automatic Genre Identification – Testing with Noise by Efstathios Stamatatos, Serge Sharoff, Marina Santini – Copyright © 2012, All rights reserved.   Citation:  Stamatatos E., Sharoff S., Santini M. (2012). Automatic Genre Identification – Testing with Noise. [White paper]. Retrieved from http://www.forum.santini.se/2012/03/white-paper-automatic-genre-identification-testing-with-noise/ The genre collections used in the experiments are available here. The reference list is here. In the experiments described below, genre classes coming from three genre collections have been used: Santinis7 (Santini, 2007). KI-04 (Meyer zu Eissen and Stein, 2004), and HGC (Stubbe and Ringlstetter, 2007). These genre collections have been created by different people, in different universities, for different purposes, with different criteria, and different notions of what genre is. Since genre is a complex concept and genre classes can be characterized in different ways, we assume that having a AGI algorithm … Read entire article »

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Mining genres with lexical affect sensing?

Post signed by: Alexander Osherenko, University of Augsburg I gained a comprehensive knowledge in emotion recognition in texts in my PhD thesis “Opinion mining and lexical affect sensing” (http://www.informatik.uni-augsburg.de/~osherenk/promotionsvortrag_english.pdf). In my opinion, this knowledge can be utilized for identifying genres of texts — I don’t think identifying emotions differs much from identifying genres. … Read entire article »

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