Abstract

In recent years, affective polarization has reached issues that were (at least previously) considered apolitical (see Rudolph & Hetherington. Affective polarization in political and nonpolitical settings. International Journal of Public Opinion Research, 33(3), 591–606, 2021. doi:10.1093/ijpor/edaa040). Perhaps the citizens’ reaction to coronavirus disease-2019 has helped to bring this relationship to its peak. This research proposes to analyze the response of YouTube users to the most popular videos on climate change, health, technology, and science in Spanish-speaking countries. To do this, the present work proposes an analysis using deep learning techniques. We selected the 50 videos with the highest number of views for each topic. Then, we adapt the linguistic models used to obtain the articles to index the degree of polarization. The strategy was twofold: first, using ratios and fluctuations between words; second, by measuring the affective distance both between the videos and the comments and between the comments prioritized by the platform’s moderation. The results show interesting data. First, the Spanish-speaking population does not behave similarly to the populations of Southern Europe, which are culturally related. Second, affective distance (which we propose is an indicator of polarization) does not grow over time and is not directly related to active participation in social media.

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