Twista – An Application for the Analysis and Visualization of Tailored Tweet Collections

Social media services like Twitter churn out user-generated content in vast amounts. The massive availability of this kind of data demands new forms of analysis and visualization, to make it accessible and interpretable. In this article, we introduce Twista, an application that can be used to create tailored tweet collections according to specific filter criteria, such as the occurrence of certain keywords or hashtags. Once the tweet collection has been created, Twista calculates basic statistics, e.g. the average tweet length or the most active user. Furthermore, the application can perform basic sentiment analysis, analyze tweets with regard to their date of publication, and analyze the communication between different Twitter users. The results of these analyses are visualized by means of the data driven documents toolkit (d3.js) and can be viewed directly in the browser, or are available for download in PDF and JSON format. We also present three exemplary use cases that illustrate the possible use of Twista for different scenarios

Tools for the Analysis and Visualization of Twitter Language Data

The microblogging service Twitter provides vast amounts of user-generated language data. In this article I give an overview of related work on Twitter as an object of study. I also describe the anatomy of a Twitter message and discuss typical uses of the Twitter platform. The Twitter Application Programming Interface (API) will be introduced in a generic, non-technical way to provide a basic under-standing of existing opportunities but also limitations when working with Twitter data. I propose a basic classification system for existing tools that can be used for collecting and analyzing Twitter data and introduce some exemplary tools for each category. Then, I present a more comprehensive work-flow for conducting studies with Twitter data, which comprises the following steps: crawling, annotation, analysis and visualization. Finally, I illustrate the generic workflow by describing an exemplary 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