The impact of valence shifters on mining implicit economic opinions

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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. © 2010 Springer-Verlag.

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Musat, C., & Trausan-Matu, S. (2010). The impact of valence shifters on mining implicit economic opinions. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6304 LNAI, pp. 131–140). https://doi.org/10.1007/978-3-642-15431-7_14

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