Publications by Tony Hirst
Experimenting With iGraph – and a Hint Towards Ways of Measuring Engagement?
For fear of being left way behind as Martin Hawksey starts to get to grips with R, (see for example how he’s using R to automate the annotation of Google Spreadsheets with calculations that don’t come readily or efficiently to hand in Google Spreadsheets itself), I thought I better try to get to grips with R’s igraph library… So here’s ...
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Visualising Activity Around a Twitter Hashtag or Search Term Using R
I think one of valid criticisms around a lot of the visualisations I post here and on my various #f1datajunkie blogs is that I often don’t post any explanatory context around the visualisations. This is partly a result of the way I use my blog posts in a selfish way to document the evolution of my own practice, but not necessarily the “so wha...
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What is the Potential Audience Size for a Hashtag Community?
What’s the potential audience size around a Twitter hashtag? Way back when, in the early days of webs stats, reported figures tended to centre around the notion of hits, the number of calls made to a server via website activity. I forget the details, but the metric was presumably generated from server logs. This measure was always totally unrel...
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More Thoughts on Potential Audience Metrics for Hashtag Communities
Following on from the sketched ideas relating to estimating the Potential Audience Size for a Hashtag Community?, here are a few quick doodles around the graph representation of the tag users – followers graph that explore the extent to which we can use quite simple counts and analyses to get a feel for how the followers of a set of hashtag use...
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Generating Twitter Wordclouds in R (Prompted by an Open Learning Blogpost)
A couple of weeks ago I saw a great example of an open learning blogpost from @katy_bird: Generating a word cloud (or not) from a Twitter hashtag. It described the trials and tribulations associated with trying to satisfy a request for the generation of a wordcloud based on tweets associated with a specific Twitter hashtag. A seemingly simple tas...
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Visualising Twitter User Timeline Activity in R
I’ve largely avoided “time” in R to date, but following a chat with @mhawksey at #dev8d yesterday, I went down a rathole last night exploring a few ways of visualising a Twitter user timeline and as a result also had a quick initial play with some time handling features of R, such as timeseries objects, and generating daily, weekly and mont...
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Visualising F1 Telemetry Data and Plotting Latitude and Longitude with ggplot Map Projections in R
Why don’t X-Y plots of latitude and longitude data look “right” compared to traditional map views? For example, here’s an X-Y scatterplot of some of Jenson Button’s McLaren telemetry data from the 2010 Australian Formula One Grand Prix: The image was generated, from a data file hosted on Google Spreadsheets, using the following R scrip...
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Doodling With a Conversation, or Retweet, Data Sketch Around LAK12
How can we represent conversations between a small sample of users, such as the email or SMS converstations between James Murdoch’s political lobbiest and a Government minister’s special adviser (Leveson inquiry evidence), or the pattern of retweet activity around a couple of heavily retweeted individuals using a particular hashtag? I spent a...
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Interest Differencing: Folk Commonly Followed by Tweeting MPs of Different Parties
Earlier this year I doodled a recipe for comparing the folk commonly followed by users of a couple of BBC programme hashtags (Social Media Interest Maps of Newsnight and BBCQT Twitterers). Prompted in part by a tweet from Michael Smethurst/@fantasticlife about generating an ESP map for UK politicians (something I’ve also doodled before – Sket...
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Fumblings with Ranked Likert Scale Data in R
The code is horrible and the visualisations quite possibly misleading, but I’m dead tired and there are a couple of tricks in the following R code that I want to remember, so here’s a contrived bit of fumbling with some data of the form: enjoyCompany tooMuchFamily 1 strongly agree strongly disagree 2 strongly agree strongly disagree 3 nei...
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