The Longer the Better? The Interplay Between Review Length and Line of Argumentation in Online Consumer Reviews
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Review helpfulness serves as focal point in understanding customers' purchase decision-making process on online retailer platforms. An overwhelming majority of previous works find longer reviews to be more helpful than short reviews. In this paper, we propose that longer reviews should not be assumed to be uniformly more helpful; instead, we argue that the effect depends on the line of argumentation in the review text. To test this idea, we use a large dataset of Amazon customer reviews in combination with a state-of-the-art approach from natural language processing that allows us to study the line of argumentation at sentence level. Our empirical analysis suggests that the frequency of argumentation changes moderates the effect of review length on helpfulness. Altogether, we disprove the prevailing narrative that longer reviews are uniformly perceived as more helpful. Retailer platforms can utilize our results to optimize their customer feedback system and to feature more useful reviews.
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