From Tweets to Results: How to obtain, mine, and analyze Twitter data by Derek Ruths (McGill University).
Since Twitter’s creation in 2006, it has become one of the most popular microblogging platforms in the world. By virtue of its popularity, the relative structural simplicity of Twitter posts, and a tendency towards relaxed privacy settings, Twitter has also become a popular data source for research on a range of topics in sociology, psychology, political science, and anthropology. Nonetheless, despite its widespread use in the research community, there are many pitfalls when working with Twitter data.
In this day-long workshop, we will lead participants through the entire Twitter-based research pipeline: from obtaining Twitter data all the way through performing some of the sophisticated analyses that have been featured in recent high-profile publications. In the morning, we will cover the nuts and bolts of obtaining and working with a Twitter dataset including: using the Twitter API, the firehose, and rate limits; strategies for storing and filtering Twitter data; and how to publish your dataset for other researchers to use. In the afternoon, we will delve into techniques for analyzing Twitter content including constructing retweet, mention, and follower networks; measuring the sentiment of tweets; and inferring the gender of users from their profiles and unstructured text.
We assume that participants will have little to no prior experience with mining Twitter or other social network datasets. As the workshop will be interactive, participants are encouraged to bring a laptop. Code examples and exercises will be given in Python, thus participants should have some familiarity with the language. However, all concepts and techniques covered will be language-independent, so any individual with some background in scripting or programming will benefit from the workshop.
Any plans to use Twitter feeds for your topic maps?
I first saw a reference to this workshop at: Do you haz teh (twitter) codez? by Ricard Nielson.