Assessing Customer Needs Based On Online Reviews: A Topic Modeling Approach

Thariq M. Jauhari, Soomin Kim, Máté Kovács, U. Serdült, V. Kryssanov
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引用次数: 3

Abstract

The fashion industry is one of the most exposed to new online trends manifesting themselves on the internet. Whereas fashion consumers used to get inspired from their preferred brand or print magazine to buy clothes, today, they are rather influenced by social media and online reviews. Online shoppers look for clothes on their own, basing their choices on individual preferences and values. In other words, consumers have become more focused on "indirect experiences" and "exploration" rather than buying products from specific brands in the store. Furthermore, consumers want to know more about the products, and the fashion market demands greater transparency. From online reviews and ratings, consumers can gather a variety of helpful subjective information from each other. This research is conducted by looking at online product review data from Amazon, one of the leading online shopping websites worldwide, to reveal the hidden topics that are available within the review texts. To do this, topic modeling is applied to the data to explore customer preferences and consumption trends. The results show that the online reviews used in this study can be grouped into four general topics discussed online: Accessories, Outfit, Quality, and Appearance. With this information available, it would benefit and improve fashion businesses in account for product development.
基于在线评论的客户需求评估:主题建模方法
时尚行业是最容易受到网络新潮流影响的行业之一。时尚消费者过去常常从他们喜欢的品牌或印刷杂志中获得灵感来购买衣服,而今天,他们更多地受到社交媒体和在线评论的影响。网上购物者根据个人喜好和价值观自己挑选衣服。换句话说,消费者更注重“间接体验”和“探索”,而不是在店内购买特定品牌的产品。此外,消费者希望更多地了解产品,时尚市场需要更大的透明度。从在线评论和评分中,消费者可以从彼此那里收集到各种有用的主观信息。这项研究是通过查看亚马逊(全球领先的在线购物网站之一)的在线产品评论数据来进行的,以揭示评论文本中可用的隐藏主题。为此,将主题建模应用于数据,以探索客户偏好和消费趋势。结果表明,本研究中使用的在线评论可以分为四个在线讨论的主题:配饰、服装、质量和外观。有了这些信息,它将有利于并改善时尚企业的产品开发。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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