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    Computer Science Department, Politehnica University of Bucharest
    Research Institute for Artificial Intelligence

    The Impact of Valence Shifters on Mining Implicit Economic Opinions

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    We investigated the influence of valence shifters on sentiment analysis within a new model built to extract opinions from economic texts. The system relies on implicit convictions that emerge from the studied texts through co-occurrences of economic indicators and future state modifiers. The polarity of the modifiers can however easily be reversed using negations, diminishers or intensifiers. We compared the system results with and without counting the effect of negations and future state modifier strength and we found that results better than chance are rarely achieved in the second case. In the first case however we proved that the opinion polarity identification accuracy is similar or better than that of other similar tests. Furthermore we found that, when applied to economic indicators, diminishers have the effect of negations.

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    Description

    Title : The Impact of Valence Shifters on Mining Implicit Economic Opinions
    Author(s) : Claudiu Musat, Stefan Trausan-matu
    Abstract : We investigated the influence of valence shifters on sentiment analysis within a new model built to extract opinions from economic texts. The system relies on implicit convictions that emerge from the studied texts through co-occurrences of economic indicators and future state modifiers. The polarity of the modifiers can however easily be reversed using negations, diminishers or intensifiers. We compared the system results with and without counting the effect of negations and future state modifier strength and we found that results better than chance are rarely achieved in the second case. In the first case however we proved that the opinion polarity identification accuracy is similar or better than that of other similar tests. Furthermore we found that, when applied to economic indicators, diminishers have the effect of negations.
    Keywords : dimi, economic predictions, opinion mining, valence shifters

    Subject : unspecified
    Area : Other
    Language : English
    Year : 2010

    Affiliations Computer Science Department, Politehnica University of Bucharest
    Journal : Forum American Bar Association
    Publisher : Springer
    Pages : 131-140
    Url : http://www.springerlink.com/index/J25M550345K66670.pdf

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    Stefan's Peer Evaluation activity

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