Exploring public attitudes of child abuse in mainland China: A sentiment analysis of China’s social media Weibo

• Published in: Children and youth services review 2020-09, Vol.116, p.105250, Article 105250
• Main Authors: Lyu, YuWen, Chow, Julian Chun-Chung, Hwang, Ji-Jen
• Format: Article
• Language: English
• Subjects: Analysis; Asian cultural groups; Attitudes; Big Data; Child abuse; Child abuse & neglect; Child protection policy; Child welfare; Children; Children & youth; China; Corporal punishment; Data mining; Emotional abuse; Emotional responses; Emotions; Enforcement; Government agencies; Keywords; Kindergarten; Mass media; Obscenity; Protection; Public attitudes; Public opinion; Punishment; Rape; Resentment; Sentiment analysis; Shame; Social media; Social networks; Technology; Vocabulary; Weibo
• ISSN: 0190-7409; 1873-7765
• DOI: 10.1016/j.childyouth.2020.105250

•Applying innovative methods of text mining to the research of child abuse through sentiment analysis.•Addressing a vital but largely understudied issue in China.•Discussing how public attitude serves as a potential impetus for the government to develop child protection policies. Influenced by traditional Confucian culture, the Chinese people believe that parents or nurturers have the right to educate their children, including physical punishment. Nowadays, child abuse has increasingly become a vital issue in China. Despite this, China still lacks a complete child protection system to protect children who are being abused. The purpose of this study was to apply sentiment analysis in text-mining technology to analyze the textual data of social media Weibo, explore people’s attitudes toward child abuse incidents and the reasons behind them, and discuss how their emotions will become the potential driving force for improving China’s child protection policies. Furthermore, the research creates a paradigm for further studies of child abuse and neglect in the big data era. Using Barbalet’s macrostructural emotion theory, this study conducted sentiment analysis of social media Weibo comments on several highly publicized child abuse cases, including the incidents of Shanxi stepmother, RYB (Red, Yellow and Blue) kindergarten, Shenzhen child abuse, and Changsha nanny child abuse. Sentiment analysis was used to extract and analyze 51,068 comments on Chinese social media Weibo. Findings revealed that the critical sentiments of Chinese people regarding child abuse in China are resentment and vengefulness. In addition, 36.9% of the emotional vocabulary was resentment, 29.1% was vengefulness, 19.5% was confidence, 11.9% was fear, and 2.6% was shame. The keywords of resentment are damage, disappointed, distressed, sad, and punish. The keywords of vengefulness are obscenity, rape, demon, devil, and dark. Incidents of child abuse caused by the inadequate child protection system in China may continue to negatively influence public opinions through social media. The main emotional response to child abuse was one of resentment and vengefulness. Through the keywords of these two emotions, this study found that resentment originates from the psychological harm caused by child abuse to children, and vengefulness originates from the insufficient enforcement by government departments in child abuse cases. This analysis may serve as a potential impetus for the government to develop