Abstract
Online video has become a relevant tool to disseminate scientific information to the public. However, in this arena, science coexists with non-scientific or pseudoscientific beliefs that can influence people’s knowledge, attitudes, and behavior. Our research sets out to find empirical evidence of the representation of pro-science, anti-science and neutral stances in online videos. From a search on Google videos, we conducted content analysis of a sample of videos about climate change, vaccines and nanotechnology (n = 826). Results indicate that a search through Google videos provides a relatively small representation of videos with an anti-science stance, which can be regarded as positive, given the high potential influence of this search engine in spreading scientific information among the public. Our research also provides empirical evidence of the fact that an anti-science stance is more frequent in user-generated content than in videos disseminated by other types of producers.
Highlights
In recent years, terminology seeking to classify messages that are favorable or contrary to established scientific knowledge have proliferated
Our results show that the videos obtained through the Google search engine are mainly positioned in favor of established scientific knowledge or display a neutral stance
Our research has provided the first empirical evidence showing that the characteristics of videos obtained through the Google search engine may differ significantly from those of YouTube
Summary
Terminology seeking to classify messages that are favorable or contrary to established scientific knowledge have proliferated. In relation to anti-science stance messages, terms such as ‘misinformation,’ ‘disinformation,’ ‘fake news’ and ‘denialism’ are applied. On the other hand, ‘science advocacy’ and ‘pro-science’ are employed to promote a stronger role of science in society. Neither positive nor negative, ‘neutral science’ and related words are descriptive and explanatory. It is not our intention to discuss or delimit these terms. Prior work has been done by other authors in this regard (e.g., Gerasimova, 2018; Lazer et al, 2018; Scheufele & Krause, 2019)
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