Social scientists are now in an era of data abundance, and machine learning tools are
increasingly used to extract meaning from data sets both massive and small. We explain …

To advance our understanding of social media effects, it is crucial to incorporate the
increasingly prevalent visual media into our investigation. In this article, we discuss the …

Voters evaluate politicians not just by what they say, but also how they say it, via facial
displays of emotions and vocal pitch. Candidate characteristics can shape how leaders use …

Previous research on the success of politicians' messages on social media has so far
focused on a limited number of platforms, especially Facebook and Twitter, and …

We provide an introduction of the functioning, implementation, and challenges of
convolutional neural networks (CNNs) to classify visual information in social sciences. This …

As fact-checking videos increasingly circulate on video-sharing platforms, more research is
needed to understand the prevalent features of such videos and how they are associated …

The challenge of disentangling political communication processes and their effects has
grown with the complexity of the new political information environment. But so have …

Provides clear guidance on leveraging computational techniques to answer social science
questions In disciplines such as political science, sociology, psychology, and media studies …

Image recognition systems offer the promise to learn from images at scale without requiring
expert knowledge. However, past research suggests that machine learning systems often …

We conduct the first large-scale study of image-based political misinformation on Facebook.
We collect 13,723,654 posts from 14,532 pages and 11,454 public groups from August …