Ours to Shape

Introduction

In the penultimate post of this series, we’ll use some unsupervised learning approaches to uncover comment clusters and latent themes among the comments to President Ryan’s Ours to Shape website.

The full code to recreate the analysis in the blog posts is available on GitHub.

Introduction

We're still analyzing the comments submitted to President Ryan’s Ours to Shape website.

In the fourth installment of this series (we’re almost done, I promise), we’ll look at the sentiment – aka positive-negative tone, polarity, affect – of the comments to President Ryan’s Ours to Shape website.

Introduction

To recap, we’re exploring the comments submitted to President Ryan’s Ours to Shape website (as of December 7, 2018).

Introduction

In the last post, we began exploring the comments submitted to the Ours to Shape website. We looked at the distribution across categories and contributors, the length and readability of the comments, and a few key words in context. While I did more exploration of the data than reported, the first post gives a taste of the kind of dive into the data that usefully proceeds analysis.

Introduction

As part of a series of workshops on quantitative analysis of text this fall, I started examining the comments submitted to President Ryan’s Ours to Shape website. The site invites people to share their ideas and insights for UVA going forward, particularly in the domains of service, discovery, and community.