A Parallel Library for Social Media Analytics

Abstract

Social media analysis is a fast growing research area aimed at extracting useful information from huge amounts of data generated by social media users. This work presents a Java library, called ParSoDA (Parallel Social Data Analytics), which can be used for developing parallel data analysis applications based on the extraction of useful knowledge from large dataset gathered from social networks. The library aims at reducing the programming skills necessary to implement scalable social data analysis applications. To reach this goal, ParSoDA defines a general structure for a social data analysis application that includes a number of configurable steps, and provides a predefined (but extensible) set of functions that can be used for each step. The paper describes the ParSoDA library and presents two case studies to assess its usability and scalability.