Automated Twitter data collecting tool for data mining in social network

Authors:
Changhyun Byun;Hyeoncheol Lee;Yanggon Kim
Affiliations:
Towson University, Towson, MD;Towson University, Towson, MD;Towson University, Towson, MD
Venue:
Proceedings of the 2012 ACM Research in Applied Computation Symposium
Year:
2012

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Abstract

Applying data mining techniques to social media can yield interesting perspectives about individual human behavior, detecting hot issues and topics, or discovering a group and community. However, it is difficult to build your own data set to apply data mining techniques without an automated data gathering system. To overcome this challenge, we developed a java-based data gathering tool that continually collects social data from Twitter. This allows us, as well as other researchers, to build our own Twitter database. In this paper, we introduce the design specifications and explain the implementation details of the Twitter Data Collecting Tool we developed. In addition, we provide an in-depth analysis of Twitter messages about various Super Bowl ads by applying data-mining techniques to a case study. The study aims to address the question of how people use Twitter and to assess the power of Twitter in terms of creating consumer interest in brands and commercials.