Clicks and Cliques. Exploring the Soul of the Community

TL;DR

This study investigates the factors influencing emotional attachment to communities across 26 US communities, using various machine learning tools and data sources to identify key drivers of community attachment.

Contribution

It provides a comparative analysis of attached versus unattached individuals and communities, highlighting the key drivers of emotional attachment beyond previous variables.

Findings

Identifies key factors driving community attachment.

Differences between attached and unattached individuals.

Variations among communities in attachment levels.

Abstract

In the paper we analyze 26 communities across the United States with the objective to understand what attaches people to their community and how this attachment differs among communities. How different are attached people from unattached? What attaches people to their community? How different are the communities? What are key drivers behind emotional attachment? To address these questions, graphical, supervised and unsupervised learning tools were used and information from the Census Bureau and the Knight Foundation were combined. Using the same pre-processed variables as Knight (2010) most likely will drive the results towards the same conclusions than the Knight foundation, so this paper does not use those variables.