Text Mining in Big Data Analytics

This mini-track recognizes the reality that global collaboration systems, social media, and information systems of all types, generate enormous amounts of unstructured textual data, including: system logs, email archives, websites, blog posts, meeting transcripts, speeches, annual reports, published material, and social media posts. While this unstructured textual data is readily available, it presents tremendous challenges to researchers trying to analyze these large bodies of text with traditional methods. Text mining in big data analytics is an increasingly important technique for an interdisciplinary group of scholars, practitioners, government officials, and international organizations. For example, the American Association for the Advancement of Science (AAAS) launched a new competition in 2014 on Big Data and Analytics within its highly competitive senior executive branch fellowship program.