Political Campaigns and Big Data

By David W. Nickerson, Todd Rogers. 2014

217 citations recorded by the source corpus.

Subfields: Communication, Political Science and International Relations, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/d81ecb0360c6d615ac327dc548528e0dd88dc458

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Political Science and International Relations

1. Hanna M. Wallach
2. Ming Yin

In Sociology and Political Science

1. Philipp Schmidt
2. Hanna M. Wallach
3. Felix Biessmann
4. Jennifer Wortman Vaughan
5. Timm Teubner

Citations in the corpus

• Understanding the Effect of Accuracy on Trust in Machine Learning Models (2019, background): “For example, researchers have trained deep neural networks to help dermatologists identify skin cancer [8], while political strategists regularly use ML-based forecasts to determine their next move [21].”
• Transparency and trust in artificial intelligence systems (2020, background): “…intelligence (AI) and machine learning (ML) have become increasingly important for aiding human decision making in various fields, including medical diagnosis, political predictions, policing, predictive maintenance, and many more (Esteva et al., 2017; Nickerson & Rogers, 2014; Susto et al., 2015).”