Tuesday, August 23, 2016

Book Review: His Majesty's Dragon by Naomi Novik

I've had His Majesty's Dragon, the first of the Temeraire series, by Naomi Novik on my to-read list for quite some time. Having dragons in the Napoleonic wars sounded like an excellent plot point: fantasy combined with history. After being reminded about the series by a colleague at work, I decided to go ahead and read it and find out what it was all about.

Read on for my full review.

Sunday, August 7, 2016

Book Review: Hyperion by Dan Simmons

Hyperion by Dan Simmons is a Hugo Award-winning novel that has been on my radar for quite some time. It was described to me as Geoffery Chaucer's Cantenbury Tales in Space and it certainly has similar elements to it. The story revolves around a band of 7 pilgrims as they travel on the world of Hyperion in the brink of war. Each has their own personal motives and one of them is a traitor, but all were selected for this special pilgrimage. They resort to telling their stories to each other to figure out why they are here and what makes them, and Hyperion, special.

Read on for my full review.

Monday, August 1, 2016

Data Science: Republican & Democratic Conventions


In the past few weeks, the two major political parties in the United States of America held their national conventions. While I couldn't listen to all the speeches, I followed the news and paid attention to the overall scene. After they were done, I decided to grab the speeches of the major speakers and see if I could find any obvious trends in their word choices, similar to what I did with my Twitter project. In this blog post, I'll discuss what I can see in the data. You can find my data and all my scripts at this GitHub repo.

Friday, July 29, 2016

Data Science: The Divided States of America



In the prior two posts, I have described how I gathered twitter data from @HillaryClinton and @realDonaldTrump, how I ran a sentiment analysis on the individual tweets, and how I performed a principal component analysis on the most commonly used words. Today, I’ll tie everything together and describe how I created a model to predict whether a given tweet belongs to either of the two candidates.

Friday, July 22, 2016

Data Science: Principal Component Analysis of Twitter Data


As described on my last blog post on this topic, I've been tracking tweets from the US presidential candidates, Hillary Clinton and Donald Trump. I've looked at the top words they used and the sentiments expressed in their tweets given their word choice. However, some words are used with others almost all the time, a notable example being a slogan like Make America Great Again. As such, it may be beneficial to look at groups of words rather than individual words. For that, I took an approach applying a Principal Component Analysis. Below I describe what this is, how I used it, and what it reveals. Do note, however, that I'm applying things I learned in astronomy to this problem rather than taking courses specific to text mining. It may be that there are better tools out there than what I've used.

Friday, July 15, 2016

Data Science: Presidential Candidates on Twitter


Over the past few months, I've been working on a little hobby data science project to explore twitter data with regards to the upcoming presidential election in the United States. The project has evolved quite a bit and detailing it in full is beyond the scope of a single blog post. As such, I've decided to split it into (at least) 3 posts. This post is the first of the series and will go over the basics of gathering data from Twitter and doing some simple text mining. The second and third posts will discuss more details of the project and show some neat visualizations I've created. I'll release all my code after the third post for any curious coders. For now, let's get started seeing what Hillary Clinton and Donald Trump's Twitter accounts are talking about.

Friday, June 17, 2016

Thursday, June 16, 2016

Book Review: A Natural History of Dragons by Marie Brennan

A Natural History of Dragons, by Marie Brennan, is the first of a series of fantasy memoirs of the Lady Trent as she explores the world and learns about dragons, among other things. I heard good things about it a few years ago and have been intrigued by it and its cover. A friend of mine at work lent me a copy (an actual physical book after so long!), so I got a chance to read it.

Read on for my full review.