Can real social epistemic networks deliver the wisdom of crowds

user-607cde9d4c775e0497f57189(2020)

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摘要
Most experimental philosophy employs small-N studies with randomization. Additional light may be shed on philosophical questions by large-scale observational studies that employ Big Data methodologies. This chapter explains and showcases the promising methodology of testimonial network analysis and visualization for experimental epistemology, arguing that it can be used to gain insights and answer philosophical questions in social epistemology. The use case is the epistemic community that discusses vaccine safety primarily in English on Twitter. In two studies, the authors show, using both statistical analysis and exploratory data visualization, that there is almost no neutral or ambivalent discussion of vaccine safety on Twitter. Roughly half the accounts engaging with this topic are pro-vaccine, while the other half is con-vaccine. The results also indicate that these two camps rarely engage with one another, and that the con-vaccine camp has greater epistemic reach and receptivity than the pro-vaccine camp. In light of these findings, the authors question whether testimonial networks as they are currently constituted on popular forums such as Twitter are living up to their promise of delivering the wisdom of crowds.
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关键词
Social epistemology,PageRank,Data science,Graph drawing,Psychology,Network analysis,Wisdom of crowds
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