Contradiction in Reviews: is it Strong or Low?

Abstract : Analysis of opinions (reviews) generated by users becomes increasingly exploited by a variety of applications. It allows to follow the evolution of the opinions or to carry out investigations on web resource (e.g. courses, movies, products). The detection of contradictory opinions is an important task to evaluate the latter. This paper focuses on the problem of detecting and estimating contradiction intensity based on the sentiment analysis around specific aspects of a resource. Firstly, certain aspects are identified, according to the distributions of the emotional terms in the vicinity of the most frequent names in the whole of the reviews. Secondly, the polarity of each review segment containing an aspect is estimated using the state-of-the-art approach SentiNeuron. Then, only the resources containing these aspects with opposite polarities (positive, negative) are considered. Thirdly, a measure of the intensity of the contradiction is introduced. It is based on the joint dispersion of the polarity and the rating of the reviews containing the aspects within each resource. The evaluation of the proposed approach is conducted on the Massive Open Online Courses collection containing 2244 courses and their 73,873 reviews, collected from Coursera. The results revealed the effectiveness of the proposed approach to detect and quantify contradictions.
Type de document :
Communication dans un congrès
ECIR - Analysis of Broad Dynamic Topics over Social Media (BroDyn), Mar 2018, Grenoble, France
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Contributeur : Sébastien Fournier <>
Soumis le : jeudi 17 mai 2018 - 09:47:17
Dernière modification le : jeudi 20 décembre 2018 - 01:26:05
Document(s) archivé(s) le : lundi 24 septembre 2018 - 19:17:39


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  • HAL Id : hal-01793873, version 1


Ismail Badache, Sébastien Fournier, Adrian-Gabriel Chifu. Contradiction in Reviews: is it Strong or Low?. ECIR - Analysis of Broad Dynamic Topics over Social Media (BroDyn), Mar 2018, Grenoble, France. 〈hal-01793873〉



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