/Emerging_Local_Policy_Trends

Natural Language Processing (NLP)

Primary LanguageHTML

Emerging Local Policy Trends

Project Overview

Identification of emerging local policy trends by analyzing mayor speeches from 2016 to 2019, leveraging NLP technique of Topic Modeling using Latent Dirichlet Allocation (LDA)

Problem and Motivation

This project idea emerged from an annual report called “States of the Cities” from the National League of Cities (NLC). For the State of the Cities report, NLC staff members have been manually tagging policy topics in mayor’s speeches to analyze emerging policy trends. We intend to help improve the efficiency of the NLC staff’s tagging process with the use of NLP topic models.

Dataset

State of the City report speeches that are given once a year by the local mayors of many cities in the United States.