Introduction to Tools and Methods for the Analysis of Twitter Data
Journal Article by Manuel Burghardt (Regensburg)
The microblogging service Twitter provides vast amounts of user-generated language data. This article gives an overview of related work that has been conducted on Twitter so far. The anatomy of a Twitter message is described and typical uses of the Twitter platform discussed. The Twitter Application Programming Interface (API) will be introduced in a generic, non-technical way to provide a basic understanding of existing opportunities but also limitations when working with Twitter data. A basic classification system for existing tools is proposed that can be used for collecting and analyzing Twitter data and introduce some exemplary tools for each category. Then, a more comprehensive workflow for conducting studies with Twitter data is presented, which comprises the following steps: crawling, annotation, analysis and visualization. Finally, the generic workflow is illustrated by describing an example study from the context of social TV research. At the end of the article, the main issues concerning tools and methods for the analysis of Twitter data are briefly addressed.
Manuel Burghardt studied Information Science and English Linguistics at the University of Regensburg. He received his PhD in Information Science and currently works as a researcher for the Media Informatics Group at the University of Regensburg. His research is focused on digital humanities (www.dhregensburg.de), social media analysis and usability engineering.