Using SEASR’s Workbench to Explore the Past, Part Three: Install Guide for Newer Users

There’s been a fair bit of interest in how to use SEASR’s MEANDRE workbench. Installation is a pinch if you’re familiar with setting up a local server and have some fluency on a command line, but if not, I thought I’d give some step-by-step instructions on how to set it up on your own computer. Ideally, you’d install this on a server, but if that’s not an option running it locally is doable.

I am not a technical writer, but if you have a bit of fluency and have patience, this should help you out!

Here are some basic step-by-step instructions for users on OS X (Linux should be pretty similar). Read more

Using SEASR’s Workbench to Explore the Past, Part Two: Was the Past a Happy Place?

As an example, taking Stephen Harper’s 2012 Throne Speech, cutting it into 20 pieces, and plotting several emotions. Bad news (i.e. austerity) bookended between joy, hope.

By Ian Milligan

[updated 10:10AM – I’ve created a quick and dirty install guide for newer users]

Was the past a happy place? Could we take a large array of information and learn whether there was an emotional content to it? I’ve been increasingly curious about how we can apply a host of tools that data miners are using on contemporary information to large repositories of historical information: could we learn something new from a distant emotional reading of the past? In this post, let’s briefly chat about sentiment analysis, or the extraction of the overall emotional state of an author. It’s all very new and introductory, but I hope to pique your interest and explore some of these ideas myself. Read more

Using SEASR’s Meandre Workbench To Explore the Past, Part One: Overview

A complicated workflow in the Meandre workbench.

This is the first of a series of posts exploring some of the work I’ve been doing with SEASR. This has been complementing my ongoing work in Mathematica, and I’m actually finding the two complement each other well. Occasionally, it’s proven fruitful to try to incorporate SEASR workflows into Mathematica, as I’m always looking for neat things to play with.

This month, I was at the University of Victoria’s Digital Humanities Summer Institute, attending the SEASR Analytics course. I’m glad I did: the tools and skills that I learned there have enabled me to set up what I consider to be a pretty top-notch suite of textual analysis tools. In this post, I just want to quickly introduce you to the environment and show you a few of the neat things that you can quickly do. Read more