极化(电化学)
政治
社会化媒体
政治学
经济补偿
公共关系
政治经济学
补偿(心理学)
社会心理学
法学
社会学
心理学
物理化学
化学
作者
Christopher A. Bail,Lisa P. Argyle,Taylor Brown,John P. Bumpus,Haohan Chen,M. B. Fallin Hunzaker,Jaemin Lee,Marcus Mann,Friedolin Merhout,Alexander Volfovsky
标识
DOI:10.1073/pnas.1804840115
摘要
Significance Social media sites are often blamed for exacerbating political polarization by creating “echo chambers” that prevent people from being exposed to information that contradicts their preexisting beliefs. We conducted a field experiment that offered a large group of Democrats and Republicans financial compensation to follow bots that retweeted messages by elected officials and opinion leaders with opposing political views. Republican participants expressed substantially more conservative views after following a liberal Twitter bot, whereas Democrats’ attitudes became slightly more liberal after following a conservative Twitter bot—although this effect was not statistically significant. Despite several limitations, this study has important implications for the emerging field of computational social science and ongoing efforts to reduce political polarization online.
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