Does Twitter know your political views? POLiTweets dataset and semi-automatic method for political leaning discovery
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Abstract (arXiv)
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.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 4 of its 26 references that are in the map. First posted on arXiv 14 Jun 2022.
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References · 4
- 2021HerBERT: Efficiently Pretrained Transformer-based Language Model for Polishcited by 51
- 2014Identifying Users with Opposing Opinions in Twitter Debatescited by 6
- 2020A Few Topical Tweets are Enough for Effective User-Level Stance Detectioncited by 2
- 2017Parsimonious Data: How a single Facebook like predicts voting behaviour in multiparty systemscited by 1
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