Looking at YouTube as a space for social protest engagement: the case of Costa Rica in times of COVID-19
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| Nhiều tác giả: | , |
|---|---|
| Định dạng: | artículo original |
| Trạng thái: | Versión publicada |
| Ngày xuất bản: | 2022 |
| Miêu tả: | This article aims to analyze the reception of social mobilization in Costa Rica, in the context of the COVID-19 pandemic, based on the online public discussion space carried out on the YouTube platform. The case study, with an exploratory and descriptive scope, takes a sample of videos referring to the social mobilization cycle registered in October 2020 and is based on a digital methods approach, using natural language processing (NLP) techniques for identification of emotional patterns, positive and negative, in the comments of the users about these protests; as well as dominant themes or topics in the online discussion, based on the construction of a textual corpus of N = 5781 comments extracted from the selected materials. The analysis reveals a generalized predominance of negative polarity in the reception space for audiovisuals; in addition, it identifies three different thematic clusters of discussion that allow to elucidate the trends of the online conversation, from the users of the platform; also, these lines of discussion are consistent with the associations between videos generated by the YouTube recommendation algorithm. Finally, the findings of this article suggest future research that focuses on the reception of social phenomena from the opinions and evaluations of users in social networks, based on the application of NLP techniques for political studies. |
| Quốc gia: | Portal de Revistas UCR |
| Tổ chức giáo dục: | Universidad de Costa Rica |
| Repositorio: | Portal de Revistas UCR |
| Ngôn ngữ: | Español |
| OAI Identifier: | oai:portal.ucr.ac.cr:article/47564 |
| Truy cập trực tuyến: | https://revistas.ucr.ac.cr/index.php/ciep/article/view/47564 |
| Từ khóa: | COVID-19 digital methods natural language processing social protest YouTube métodos digitales procesamiento de lenguaje natural protesta social |