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Cognitive Biases in Link Sharing Behavior and How to Get Rid of Them: Evidence from the 2019 Spanish General Election Twitter Conversation

机译:链接共享行为中的认知偏见以及如何摆脱它们:来自2019年西班牙语一般选举的证据Twitter谈话

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After a few years focusing on issues such as electoral prediction through social media data, many analysts turned their attention toward fake news spreading and misinformation. A coherent next step in elections research through social media data would be identifying what makes communities and individuals less open to manipulation. Misinformation is not simply bad or false information but selective information circulated among isolated and unconnected groups. Here, I will discuss common cognitive biases in link sharing behavior and its effects on politically shaped communities in the Twitter public debate on the 2019 Spanish general election campaign. Finally, I will present and discuss some data-driven mechanisms that may contribute to the mitigation of mass manipulation.
机译:几年后,专注于通过社交媒体数据等选举预测等问题,许多分析师将他们的注意力转向假新闻传播和错误信息。通过社交媒体数据一致的选举研究的一个连贯的选择研究将识别使社区和个人对操纵开放的原因。误导不是简单的坏或虚假信息,而是在孤立和未连接的群体中循环的选择性信息。在这里,我将讨论链接共享行为中的共同认知偏见,以及2019年西班牙大选活动的Twitter公开辩论中对政治形态社区的影响。最后,我将展示并讨论一些可能有助于减轻大规模操纵的数据驱动机制。

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