Tiktok Talks Trash: Analyzing Public Sentiment of Waste4change's Social Entrepreneur Mission
DOI:
https://doi.org/10.55927/eajmr.v4i11.472Keywords:
Public Sentiment, NLP, Social Marketing, Social Entrepreneur, Social MediaAbstract
This study aims to uncover the public's sentiment towards the social entrepreneurship mission of Waste4Change. This study used the Natural Language Processing (NLP) approach, utilizing Word Cloud Analysis and Sentiment Score Analysis, on 615 comments about Waste4Change's mission on TikTok. The results showed that the most dominant words were waste, government, throw, trash, can, bottles, plastic, and garbage. Then, there is a negative sentiment of 96.89% towards the Waste4Change mission, due to the emergence of skepticism among TikTok users towards people's behavior and the government's seriousness in waste management. Meanwhile, positive sentiment only has a portion of 3.11% with support for the provision of facilities, systems and rewards for active participation. The implications of the research enrich the theoretical framework in the development of Social Marketing. This study is limited to the scope of the sentiment of Waste4Change's mission. Future research could reach a wider audience of social entrepreneurs.
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