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Extracting sentiment attitudes from analytical texts via piecewise convolutional neural network

Authors: Rusnachenko, N.L. and Loukachevitch, N.V.

Journal: CEUR Workshop Proceedings

Volume: 2277

Pages: 186-192

ISSN: 1613-0073

Abstract:

For deep text understanding, it is necessary to explore the connections between text units mentioning events, entities, etc. Depending on the further goals, it allows to consider the text as a graph of task-specific relations. In this paper, we focused on analysis of sentiment attitudes, where the attitude represents a sentiment relation from subject towards object. Given a mass media article and list of mentioned named entities, the task is to extract sentiment attitudes between them. We propose a specific model based on convolutional neural networks (CNN), independent of handcrafted NLP features. For model evaluation, we use RuSentRel 1.0 corpora, consisted of mass media articles written in Russian.

Source: Scopus