Over the last several years, the researchers of diverse communities focused on mining knowledge or other interested targets from structured, semi-structured, textual, multimedia or interaction data that have grown significantly. However, these massive, heterogeneous and non-synchronous data introduce significant challenges to the data, text, web, and social network mining, for example, data modeling and massive data process. How to achieve efficient, accurate, trustworthy, distributed and parallel mining results has become crucial of importance that significantly impacts its future success.
In recent years, data, text, web, and social network mining (DTWSM) has been paid an increasing attention and gained serious studies towards being successfully applied in the practice of the data incentive applications and services. DTWSM workshop aims to bring together researchers and practitioners to address various aspects of heterogeneous data mining, such as models and technologies for statistical data analysis, Web search technology, analysis of user behavior, social network analysis, data visualization, applications that touch our daily lives, and more. Together, we will continuously explore and discuss the latest academic and industrial research results related to this domain.