Archive of month: March 2013

Analysing #pydata, London and Brighton tweets for concept mapping

Below I’ve visualised tweets for #PyData conference and the cities of London and Brighton – this builds on my ‘concept cloud‘ from a few days ago at the #PyCon conference. Props to Maksim for his Social Media Analysis tutorial for inspiration. Update – Maksim’s Analying Social Networks tutorial video is online. For the earlier #PyCon […]

Semantic map of PyCon2013 Twitter Topics

Maksim taught a lovely Social Graph Analytics course at PyCon the day before I taught Applied Parallel Computing. I took his demo for a “poor mans LDA/LSI analysis” of a Twitter topic (rather than using full LDA it just uses co-incident hashtags) and added usernames to produce the plot below. Update – Analysing #pydata conference […]

PowerPoint: Brief Introduction to NLProc. for Social Media

For my client (AdaptiveLab) I recently gave an internal talk on the state of the art of Natural Language Processing around Social Media (specifically Twitter and Facebook), having spent a few days digesting recent research papers. The area is fascinating (I want to do some work here via my as the text is so […]

ANN: twitter-text-python release (Python Tweet parsing library)

A few weeks back I took over as maintainer of the twitter-text-python library (source on github). This library lets you take a tweet like: "@ianozsvald, you now support #IvoWertzel's tweet ... parser!" and extract the Twitter entities as defined in the Twitter conformance tests. The entities in the above tweet would be: reply: 'ianozsvald' […]