Pablo Barberá

Computational Political Scientist

I have ten years of experience programming in R and Python, manipulating large-scale database systems using SQL/Presto/Hive/BigQuery, developing production-ready machine learning / AI tools for user inferences, conducting statistical modeling, designing online field experiments, and producing compelling data visualizations. I am also an active contributor to the open source community and I have authored several R packages, some available on CRAN, that interact with the Twitter, Facebook, and Instagram APIs. Follow the links below for tutorials on some of the tools I have built.

streamR

This R package, available on CRAN, provides access to Twitter's Streaming API via R. See the vignette for a tutorial on how to use it. The latest version is on this GitHub repository.

scholarnetwork

This R package, available on GitHub extracts publication information from Google Scholar to produce a visualization of collaboration ego networks. See the README for a tutorial on how to use it.

tweetscores

R package that provides a series of functions to collect and analyze Twitter data, and to estimate the ideological positions of Twitter users. See GitHub repository for latest version and documentation.

pytwools

Python tools for the analysis of Twitter data in JSON format or in MongoDB collections, and network visualization using Gephi. See GitHub repository.

For more code and other materials, check my GitHub repositories