Text Mining Analysis on Users' Reviews for News Aggregator Toutiao
: Li Jia, Wang Bifeng, Ni Alexandra Jingsi, Liu Qian
: Laura Tan, Jianglian Zhao
: International Conference on Artificial Intelligence and Cloud Computing
Publisher: IOP Publishing Ltd
: 2021
: Journal of Physics: Conference Series
: International Conference on Artificial Intelligence and Cloud Computing (ICAICC) 2020 18-20 December 2020, Suzhou, China
: Journal of Physics: Conference Series
: Journal of Physics: Conference Series
: 1771
: 012008
: 1742-6588
DOI: https://doi.org/10.1088/1742-6596/1771/1/012008(external)
: https://iopscience.iop.org/article/10.1088/1742-6596/1771/1/012008(external)
: https://research.utu.fi/converis/portal/detail/Publication/54797029(external)
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