The 4th International Workshop on Data, Text, Web, and Social Network Mining

(DTWSM 2017)

Helsinki, Finland, 21-23 August, 2017

A variety of data to be processed continues to witness a quick increase. Effective management and analysis of large-scale data poses an interesting but critical challenge. Parallel processing frameworks and cloud computing were presented to store and process such problems. Various data generated constantly by users are consisted of textual, multimedia and usage records/logs, social interaction data also included. Multitudinous data sources spring up for knowledge mining, targets tracking or relationships analysis which ultilize the techniques of data mining. Nevertheless, a significant challenge emerges when facing the data, text, web, and social network mining introduced by these massive, heterogeneous and non-synchronous data. For example, generic data modeling and massive data process. To obtain efficient, accurate, trustworthy, distributed and parallel mining results is becoming increasingly crucial since future success of applications significantly depends on and benefits from data mining and its intelligence.

In this decade, 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. This forum is founded to promote closer exchange between researchers and professionals from worldwide academia and industry for showcasing, discussing, and reviewing the whole spectrum of technological opportunities, challenges, solutions, and emerging applications in this research area.

Topics of interest include, but are not limited to:

  1. Information indexing and retrieval
  2. Theoretic foundations of heterogeneous data mining
  3. Mining heterogeneous/multi-source data
  4. User behavior analysis
  5. Mining spatial and temporal data
  6. Mining unstructured and semi-structured data
  7. Mining social networks
  8. Mining high dimensional data
  9. Mining uncertain data
  10. Mining imbalanced data
  11. Mining dynamic/streaming data
  12. Personalization, privacy and security
  13. Opinion mining and sentiment analysis
  14. Human, domain, organizational and social factors in data mining

Important Dates

Submission Deadline extended to: 15 May, 2017
Paper submission deadline: 15 April, 2017
Internal Reviews to be completed: 1 June, 2017
Author notification: 3 June, 2017
Camera-ready and Registration: 18 June, 2017
Conference dates: 21-23 August, 2017

Submission Instructions

Submitted papers must not substantially overlap with papers that have been published or that are simultaneously submitted to a journal or a conference with proceedings. Papers must be clearly presented in English, must not exceed 10 pages (extra pages will be charged), including tables, figures, references and appendixes, in Springer LNCS Format with Portable Document Format (.pdf). Please submit your paper at:

Papers will be selected based on their originality, timeliness, significance, relevance, and clarity of presentation. Submission of a paper should be regarded as a commitment that, should the paper be accepted, at least one of the authors will register and attend the conference to present the work. The workshop paper will be involved into the ICA3PP2017 proceedings published by Springer Lecture Notes in Computer Science (LNCS, EI indexed). Excellent Papers will be recommended to high-quality journal special issues (SCI/SCIE indexed).

Program Co-Chairs

PC Members (In alphabetical order)


Please email inquiries concerning DTWSM2017 to:
Prof. Jun Liu, Email: