A4 Refereed article in a conference publication
Text Mining Analysis on Users' Reviews for News Aggregator Toutiao
Authors: Li Jia, Wang Bifeng, Ni Alexandra Jingsi, Liu Qian
Editors: Laura Tan, Jianglian Zhao
Conference name: International Conference on Artificial Intelligence and Cloud Computing
Publisher: IOP Publishing Ltd
Publication year: 2021
Journal: Journal of Physics: Conference Series
Book title : International Conference on Artificial Intelligence and Cloud Computing (ICAICC) 2020 18-20 December 2020, Suzhou, China
Journal name in source: Journal of Physics: Conference Series
Series title: Journal of Physics: Conference Series
Volume: 1771
First page : 012008
ISSN: 1742-6588
DOI: https://doi.org/10.1088/1742-6596/1771/1/012008
Web address : https://iopscience.iop.org/article/10.1088/1742-6596/1771/1/012008
Self-archived copy’s web address: https://research.utu.fi/converis/portal/detail/Publication/54797029
This paper intent to improve consumer communication by text mining analysis
with users’ reviews. The news aggregator we focus on is: Toutiao, known as “today's
headlines” in Chinese. It is the top news aggregator application run by Bytedance
company in China. It utilizes AI algorithms to provide numerous news feed for its users. As new technologies are shaping the business strategy studies as well as online
communication analysis, it requires innovative and effective analyses of unconventional
data, such as the 12,290 online reviews on Toutiao we collected from Apple’s App Store. Through the LDA topic modelling and sentiment analysis, our research has identified three
major negative complains the consumers have regarding Toutiao application, namely: too
many unsolicited advertisements, contents (vulgar content, time consuming video, privacy
and copyrights infringement issue) and incompatibility with the latest Apple digital
devices
Downloadable publication This is an electronic reprint of the original article. |  |
