Topic models have been applied to everything from books to newspapers to social media
posts in an effort to identify the most prevalent themes of a text corpus. We provide an in …

Democracies are postulated upon the ability to carry out fair elections, free from any form of
interference or manipulation. Social media have been reportedly used to distort public …

This article investigates the prevalence of high and low quality URLs shared on Twitter when
users discuss COVID-19. We distinguish between high quality health sources, traditional …

The rising prevalence of fake news and its alarming downstream impact have motivated
both the industry and academia to build a substantial number of fake news classification …

This study is the first to evaluate e-government diffusion among local governments in the
United States over time. The diffusion rates of various types of e-government services are …

Transformer-based models have become the state-of-the-art for numerous natural language
processing (NLP) tasks, especially for noisy data sets, including social media posts. For …

There is widespread concern that political “deepfakes”—fabricated videos synthesized by
deep learning—pose an epistemic threat to democracy as a uniquely credible form of …

Research in political science suggests campaigns have a minimal effect on voters' attitudes
and vote choice. We evaluate the effectiveness of the 2016 Trump and Clinton campaigns at …

Purpose This study investigates drivers of local governments' digitalization, focusing on
contextual factors that can help explain the level of e-government development. Concretely …

Larry Lessig argues that four modes regulate behavior in cyberspace: laws, markets, norms,
and architecture. How can these four modes regulate the production and spread of fake …