| Autor: |
Ruei-Shan Lu, Hsiu-Yuan Tsao, Hao-Chaing Koong Lin, Yu-Chun Ma, Cheng-Tung Chuang |
| Rok vydání: |
2022 |
| Popis: |
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. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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