Researchers from Indiana University Bloomington, IN, have developed a tool assisting social sciences researchers lacking technical know-how to get insights into the behavior and community layout from the individual posts of thousands of users from Twitter data.
What Truthy accomplishes is to monitor in real-time tweets and to cluster them in groups, called “memes”. Those memes are generated when there is a common hashtag, mentioned Twitter user, hyperlink or a phrase. This information is derived from previously hand-picked keywords.
The tool provides various visualizations for understanding network topology and trends, number of users and tweets, information diffusion, degree measurements, largest connected component, geography and time, and meme occurrence patterns, sentiment score, language and user activity.
But more than that – it allows the data to be downloaded in .CSV format for further research and to be imported in other tools.
The tool also provides an API through Mashable with the option to get information about users, memes, networks and timelines. There are plans of further improving the API, expanding the data repository and allowing for better visualizations.
Truthy is really useful, especially for political scientists and journalists who want to understand underlying network structures and information diffusion patterns.