4 citations · 7 across the 3 of their papers we have counts for
5 papers
Fuzzy Forests For Feature Selection in High-Dimensional Survey Data: An Application to the 2020 U.S. Presidential Election
Sreemanti Dey, R. Michael Alvarez
An increasingly common methodological issue in the field of social science is high-dimensional and highly correlated datasets that are unamenable to the traditional deductive frame…
Dynamic Social Media Monitoring for Fast-Evolving Online Discussions
Maya Srikanth, Anqi Liu, Nicholas Adams-Cohen +3
Tracking and collecting fast-evolving online discussions provides vast data for studying social media usage and its role in people's public lives. However, collecting social media…
FREEtree: A Tree-based Approach for High Dimensional Longitudinal Data With Correlated Features
Yuancheng Xu, Athanasse Zafirov, R. Michael Alvarez +3
This paper proposes FREEtree, a tree-based method for high dimensional longitudinal data with correlated features. Popular machine learning approaches, like Random Forests, commonl…
Reliable and Efficient Long-Term Social Media Monitoring
Jian Cao, Nicholas Adams-Cohen, R. Michael Alvarez
Social media data is now widely used by many academic researchers. However, long-term social media data collection projects, which most typically involve collecting data from publi…
Finding Social Media Trolls: Dynamic Keyword Selection Methods for Rapidly-Evolving Online Debates
Anqi Liu, Maya Srikanth, Nicholas Adams-Cohen +2
Online harassment is a significant social problem. Prevention of online harassment requires rapid detection of harassing, offensive, and negative social media posts. In this paper,…