JSAI2020

Presentation information

Organized Session

Organized Session » OS-2

[1F3-OS-2a] OS-2 (1)

Tue. Jun 9, 2020 1:20 PM - 3:00 PM Room F (jsai2020online-6)

野中 朋美(立命館大学)、藤井 信忠(神戸大学)

1:40 PM - 2:00 PM

[1F3-OS-2a-02] Semantic Analysis of Sizzle Words Based on Customer Reviews for Foods Using a Word2vec

〇Fumiaki SAITOH1 (1. Chiba Institute of Technology)

Keywords:Sizzle Words, Text Mining, Neural network

The purpose of this study is to analyze the meaning of Sizzle words that induce consumer appetites and their willingness to purchase. Semantic analysis of these words is important because they are widely used in various stages of marketing, such as advertising, packaging, catch copy, and product development. In this study, we adopt “Word2Vec,” which is a tool used for vectorization of the semantic structure of words. A semantic model is constructed using Word2Vec and is adapted to online food reviews (provided by customers) and includes representative Sizzle words. The semantic analysis of the relation between sizzle words and the surrounding words based on Word2Vec may lead to the discovery of novel Sizzle words and their usages.

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