Show me your friends, and I will tell you whom you vote for: Predicting voting behavior in social networks

Lihi Idan, J. Feigenbaum
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引用次数: 13

Abstract

Increasing use of social media in campaigns raises the question of whether one can predict the voting behavior of social-network users who do not disclose their political preferences in their online profiles. Prior work on this task only considered users who generate politically oriented content or voluntarily disclose their political preferences online. We avoid this bias by using a novel Bayesian-network model that combines demographic, behavioral, and social features; we apply this novel approach to the 2016 U.S. Presidential election. Our model is highly extensible and facilitates the use of incomplete datasets. Furthermore, our work is the first to apply a semi-supervised approach for this task: Using the EM algorithm, we combine labeled survey data with unlabeled Facebook data, thus obtaining larger datasets as well as addressing self-selection bias.
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给我看看你的朋友,我就会告诉你你投给谁:预测社交网络中的投票行为
社交媒体在竞选活动中的使用越来越多,这引发了一个问题:人们能否预测那些没有在网上个人资料中披露政治偏好的社交网络用户的投票行为?在此之前的工作只考虑那些生成政治导向内容或自愿在网上披露其政治偏好的用户。我们通过使用一种新颖的贝叶斯网络模型来避免这种偏差,该模型结合了人口统计、行为和社会特征;我们将这种新方法应用于2016年美国总统大选。我们的模型具有高度的可扩展性,并且便于使用不完整的数据集。此外,我们的工作是第一个将半监督方法应用于该任务的:使用EM算法,我们将标记的调查数据与未标记的Facebook数据结合起来,从而获得更大的数据集,并解决自我选择偏差。
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