Every day, the world is flooded by millions of messages and statements posted on Twitter or Facebook. Social media platforms try to protect users' personal data, but there still is a real risk of misuse, including elections manipulation. Did you know, that only 13 posts addressing important or controversial topics for society are enough to predict one's political affiliation with a 0.85 F1-score? To examine this phenomenon, we created a novel universal method of semi-automated political leaning discovery. It relies on a heuristical data annotation procedure, which was evaluated to achieve 0.95 agreement with human annotators (counted as an accuracy metric). We also present POLiTweets - the first publicly open Polish dataset for political affiliation discovery in a multi-party setup, consisting of over 147k tweets from almost 10k Polish-writing users annotated heuristically and almost 40k tweets from 166 users annotated manually as a test set. We used our data to study the aspects of domain shift in the context of topics and the type of content writers - ordinary citizens vs. professional politicians.

研究发现，使用社交媒体平台的用户只需发表13篇与社会相关的帖子即可预测其政治取向，作者通过创新的半自动化方法来发现用户的政治倾向，并公开了波兰的POLiTweets数据集，以研究多党制的政治倾向和领域转移等问题。

Twitter 是否知道你的政治观点？POLiTweets 数据集和半自动方法的政治倾向发现