I decided to replicate the showing/hiding the dominant hues in images with showing/hiding around the average RGB values instead. I created a class called RGBColor (just holds red, green, and blue values), similar to the one I created called HSBColor. I could have used the java.awt.Color class, but that insists on a range of 0-1 […]
I thought it would be interesting to invert the idea of showing only the dominant hue, and show everything but that instead. I used the exact same code, but inverted the if statement so: if (!hueInRange(hue, lower, upper)) became if (hueInRange(hue, lower, upper)) Effect is as follows, as with most of these, my favourite effect […]
Having extracted the dominant hue from the images, we can manipulate the image such that pixels that are not (or close to) the dominant hue are instead made grayscale. I converted to grayscale using the brightness of the image in the HSB. This worked really nicely. From my earlier experiments I decided on a hue […]
I wanted to explore temporal rhythms around the conference, for example to pick out more popular or particularly tweet-able sessions. Color scheme: Is directed at someone by starting with an @ Contains a mention (@) of someone else Contains a link Disappointingly, no patterns are immediately obvious here – it seems like tweeting was reasonably consistent throughout. I […]
I’m working on a paper on topical communities, and as part of that I’ve come back to this dataset to explore the social network that emerges through @ mentions. To start with, I looked at the social network that emerges when we look at the people on the list. This network is pretty densely connected, […]
For a while, I’ve been wanting to make something that explores color in photo sets. Reading Beautiful Visualization (Amazon), I came across the perfect way to arrange the elements. It imitates the layout of the sunflower seeds, “the most efficient and visually mesmerizing way of packing small elements into a large circle”. I decided to […]
Unfortunately I can’t post the actual paper for a year, but hopefully the talk is going to be more interesting anyway! I used Google Docs to create my slides and you can find the deck here. Twitter: An Overview Who doesn’t use Twitter? Who doesn’t use Twitter because they think it’s pointless? Before I start, […]
Continued on from this post. Also see my supervisor’s comments. Interestingly, it turns out there is an Eclipse product called “Eclipse RT”, so perhaps there weren’t as many retweets as the wordle might have suggested… Still – 413 of the 640 tweets in the data set contained an @ mention of some kind. Of these, […]
My supervisor had the idea of grabbing a conference dataset by hashtag, specifically the Eclipse Conference 2010 (hashtag #ese) which took place in Ludwigsburg, Germany, November 2nd to November 4th. You can get an idea of what people were talking about in the wordle, below (applet is here): Apparently there were a lot of RT’s. We’ll […]
I used the Classifier4J Summarizer to summarize the tweets and pick out the 5 tweet summary of the period, and the 1 tweet summary of @ replies and non-directed tweets. Only letters and spaces were kept for the summary (thus each tweet was treated as one sentence), the summarizer transforms everything to lower case and […]