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Sentiment Analysis of Brand Personality Positioning Through Text Mining
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Author(s): Ruei-Shan Lu (Takming University of Science and Technology, Taipei, Taiwan), Hsiu-Yuan Tsao (National Chung Hsing University, Taiwan), Hao-Chaing Koong Lin (National University of Tainan, Tainan, Taiwan), Yu-Chun Ma (National University of Tainan, Tainan, Taiwan)and Cheng-Tung Chuang (Takming University of Science and Technology, Taipei, Taiwan)
Copyright: 2022
Pages: 12
Source title:
Research Anthology on Implementing Sentiment Analysis Across Multiple Disciplines
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-6684-6303-1.ch045
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Abstract
This article uses text mining and a Chinese word segmentation program developed by the Chinese Knowledge and Information Processing Group in Taiwan's Academia Sinica to analyze Facebook posts from 14 e-commerce companies. In addition, a list of keywords representing brand personalities is analyzed to reveal key factors affecting which social media posts attract consumers' attention. This research uses statistical analysis with a nonmanual questionnaire that is efficient and based on computer science to provide a reference for businesses operating Facebook fan pages and internet marketing.
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