DiSH: Democracy in State Houses

<p>In our current political climate, state level legislators have become increasingly impor- tant. Due to cuts in funding and growing focus at the national level, public oversight for these legislators has drastically decreased. This makes it difficult for citizens and activists to understand the relationships and commonalities between legislators. This thesis provides three contributions to address this issue. First, we created a data set containing over 1200 features focused on a legislator’s activity on bills. Second, we created embeddings that represented a legislator’s level of activity and engagement for a given bill using a custom model called Democracy2Vec. Third, we provided a case study focused on the 2015-2016 California State Legislator and had our results verified by a political expert. Our results show that our embeddings can explain relationships between legislator and how they will likely act during the legislative process.</p>

Name thesis:degree_name

MS in Computer Science

Discipline thesis:degree_discipline

Computer Science

Year dc:date.available

2019

Author dc:creator

• Russo, Nicholas A

Contributors dc:contributor

• Alex Dekhtyar

• Digital Democracy
• Machine Learning
• Embeddings
• Neural Networks
• Clusterings
• American Politics
• Artificial Intelligence and Robotics
• Databases and Information Systems
• Software Engineering
• Theory and Algorithms

Identifier

10.15368/theses.2018.157

OAI identifier oai:identifier

oai:digitalcommons.calpoly.edu:theses-3358