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Open AccessJournal ArticleDOI

Social media and microtargeting: Political data processing and the consequences for Germany:

TLDR
This paper explores the possibility to identify micro groups of users, which can potentially be targeted with special campaign messages, and how this approach can be expanded to large parts of the electorate, and discusses the ethical and political implications for the German political system.
Abstract
Amongst other methods, political campaigns employ microtargeting, a specific technique used to address the individual voter. In the US, microtargeting relies on a broad set of collected data about ...

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Proceedings ArticleDOI

Dancing to the Partisan Beat: A First Analysis of Political Communication on TikTok

TL;DR: It is illustrated that political communication on TikTok is much more interactive in comparison to other social media platforms, with users combining multiple information channels to spread their messages.
Journal ArticleDOI

Privacy, Big Data, and the Public Good: Frameworks for Engagement

TL;DR: Big Data is a Big Deal; hence the Big Book; hence, this Big Book.
Journal ArticleDOI

Political communication on social media: A tale of hyperactive users and bias in recommender systems

TL;DR: It is quantitatively demonstrated that hyperactive users have a significant role in the political discourse: They become opinion leaders, as well as having an agenda-setting effect, thus creating an alternate picture of public opinion.
Proceedings ArticleDOI

The Rise of Germany's AfD: A Social Media Analysis

TL;DR: In 2017, the Alternative fur Deutschland (AfD) became the third largest party in the government and used all available social media channels to spread the AfD's message.
References
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Journal ArticleDOI

Latent dirichlet allocation

TL;DR: This work proposes a generative model for text and other collections of discrete data that generalizes or improves on several previous models including naive Bayes/unigram, mixture of unigrams, and Hofmann's aspect model.
Proceedings Article

Latent Dirichlet Allocation

TL;DR: This paper proposed a generative model for text and other collections of discrete data that generalizes or improves on several previous models including naive Bayes/unigram, mixture of unigrams, and Hof-mann's aspect model, also known as probabilistic latent semantic indexing (pLSI).
Journal ArticleDOI

Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images

TL;DR: The analogy between images and statistical mechanics systems is made and the analogous operation under the posterior distribution yields the maximum a posteriori (MAP) estimate of the image given the degraded observations, creating a highly parallel ``relaxation'' algorithm for MAP estimation.
BookDOI

Markov Chain Monte Carlo in Practice

TL;DR: The Markov Chain Monte Carlo Implementation Results Summary and Discussion MEDICAL MONITORING Introduction Modelling Medical Monitoring Computing Posterior Distributions Forecasting Model Criticism Illustrative Application Discussion MCMC for NONLINEAR HIERARCHICAL MODELS.
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