Data analysis of resident engagement and sentiments in social media enables better household waste segregation and recycling

被引:23
作者
Jiang, Peng [1 ]
Zhou, Jieyu [2 ,5 ]
Van Fan, Yee [3 ]
Klemes, Jirf Jaromfr [3 ]
Zheng, Meimei [4 ]
Varbanov, Petar Sabev [3 ]
机构
[1] Sichuan Univ, Business Sch, Dept Ind Engn & Engn Management, Chengdu 610064, Peoples R China
[2] Natl Univ Singapore, NUS Environm Res Inst NERI, Singapore 117411, Singapore
[3] Brno Univ Technol VUT Brno, Fac Mech Engn, NETME Ctr, Sustainable Proc Integrat Lab, Tech 2896-2, Brno 61669, Czech Republic
[4] Shanghai Jiao Tong Univ, Sch Mech Engn, Dept Ind Engn & Management, Shanghai 200240, Peoples R China
[5] Campus Res Excellence & Technol Enterprise CREATE, Energy & Environm Sustainabil Megacities E2S2 Pha, 1 CREATE Way, Singapore 138602, Singapore
基金
新加坡国家研究基金会; 中国国家自然科学基金;
关键词
Increased waste recycling; Waste reduction; Digitalised waste management; Resident engagement; Social media; Data analysis; MUNICIPAL SOLID-WASTE;
D O I
10.1016/j.jclepro.2021.128809
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Waste segregation, recycling and reduction have been prioritised in the Circular Economy transition of household waste management to reduce environmental impacts. With digitalisation and innovation developments in waste management, residents become more active on waste management-related social media platforms. However, there is still needed a tangible analysis of resident engagement (e.g. user comments and interactions) and related sentiment changes on such platforms to enhance waste management and ease the environmental burden at source. This study develops an integrated solution to analyse resident engagement by leveraging statistical analysis and text-mining methods. Four interrelated components are incorporated in the solution: population behaviour quantification, sentiment analysis and dynamics, popular concerns and probability distribution fitting, and rule-based managerial insight identification. The novel solution is applied to a real-world case study on a subscription account related to waste management in Shanghai. This research produces several major observations based on the studied case: (i) The resident engagement Monday-to-Thursday was more active than Friday-to-Sunday. (ii) Compared to 2018, the resident engagement by commenting on online posts was elevated by 107.1% in 2019 when Shanghai introduced a new management policy. Meanwhile, the yearly resource-type waste collection was increased by 114.5% in 2019. (iii) It took approximately one year to recover positive sentiments in user comments after introducing the policy. However, the comments with negative sentiments assisted in improving waste management. (iv) The best-fitted negative binomial distribution of the number of votes for user comments could guarantee the managerial insight identification from the minority of comments with popular concerns.
引用
收藏
页数:12
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