Mining Negativity from Online Reviews: A Comparison between Search and Experience Goods (original) (raw)

SSRN Electronic Journal, 2000

Abstract

ABSTRACT Online consumer reviews constitute an integral aspect of electronic transactions as they play a part in lowering customer uncertainty during purchase decision making. This paper studies the aspect of negativity exhibited on the justification of its valence by the review text (as a dependent variable) and the influence of product price and product type to either an experience or a search good and across the values of the review rating scale on a dataset consisting of N=667 products with a minimum number of 15 reviews per product. The study uses novel opinion mining methodology based on a phrase-based opinion list that has been extracted from a large corpus of online consumer reviews gathered from the German site of Amazon (Amazon.de). The study also provides (1) empirical evidence that product type (experience or search good) affects review text negativity, with experience goods receiving higher amounts of negative text in relation with search goods and (2) that higher product price results to fewer negative statements in the review text. The paper also provides discussion of the findings and practical implications in relation with the IS literature.

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