Text Mining Analysis on Users’ Reviews for News Aggregator Toutiao

Autor:	Qian Liu, Alexandra Jingsi Ni, Bifeng Wang, Jia Li
Rok vydání:	2021
Předmět:	Topic model History Focus (computing) Emerging technologies Computer science Sentiment analysis computer.software_genre App store Computer Science Applications Education News aggregator World Wide Web Communication Analysis Strategic management computer
Zdroj:	Journal of Physics: Conference Series. 1771:012008
ISSN:	1742-6596 1742-6588
DOI:	10.1088/1742-6596/1771/1/012008
Popis:	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.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::c0c2baa7628af4042c4992dd8450a825 https://doi.org/10.1088/1742-6596/1771/1/012008 Zobrazit plný text záznamu