openThis study aims to investigate the presence of anti-scientific behavior in user-generated reviews of scientific documentaries. The primary objective is to assess whether the COVID-19 pandemic has influenced individuals' anti-scientific tendencies.
By analyzing a dataset of user reviews gathered from various online platforms, the study employs natural language techniques to identify patterns and linguistic cues indicative of anti-scientific sentiments.
Furthermore, the study incorporates econometric models, specifically fixed effects models. These models allow for the control of individual-specific characteristics and time-related variations, enabling a robust examination of the relationship between the COVID-19 pandemic and anti-scientific behavior in documentary reviews.
The findings of this study not only contribute to our understanding of public attitudes towards science but also shed light on the impact of major global events, such as the COVID-19 pandemic, on anti-scientific sentiments.This study aims to investigate the presence of anti-scientific behavior in user-generated reviews of scientific documentaries. The primary objective is to assess whether the COVID-19 pandemic has influenced individuals' anti-scientific tendencies.
By analyzing a dataset of user reviews gathered from various online platforms, the study employs natural language techniques to identify patterns and linguistic cues indicative of anti-scientific sentiments.
Furthermore, the study incorporates econometric models, specifically fixed effects models. These models allow for the control of individual-specific characteristics and time-related variations, enabling a robust examination of the relationship between the COVID-19 pandemic and anti-scientific behavior in documentary reviews.
The findings of this study not only contribute to our understanding of public attitudes towards science but also shed light on the impact of major global events, such as the COVID-19 pandemic, on anti-scientific sentiments
