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Big Data in Human Behaviour Research: a Contextual Turn?

Journal of Big Data welcomes submissions to the thematic series "Big Data in Human Behaviour Research: a Contextual Turn?" 

Despite its considerable contributions, big data analytics has long been criticized for the lack of systematic contextual consideration. In other words, scholarships in data science methods may suffer from the pitfall of not unpacking, recognizing, and theorizing the richness of contextual elements in (big) data, thereby risking ignoring the complexity and variability among individuals, groups, and cultures. In particular, scholarly work on the contextualization of data from a wide range of disciplines like data science, medical science, and human science has not been reciprocally and reflectively articulated yet. 

Potential topics include but are not limited to:

  • challenges and opportunities in big data analytics, such as the risks and pitfalls of ignoring context/contextualization
  • context-aware approach in data science research
  • the measurement and integration of, for instance, linguistic and cultural diversity in computational methods
  • meanings and models of contextualization in big data analytics 
  • innovations and advancements of machine Deep Learning (DL) in identifying latent information in Natural Language Processing (NLP) research

Important Dates 
Deadline to submit an abstract to the editors: 1 July 2023
Full manuscript submission deadline: 1 October 2023

Lead Guest Editor
Jun Liu, University of Copenhagen, Denmark

Guest Editors 
Xianwen Kuang, Xi'an Jiaotong-Liverpool University, China
Simon Schweighofer, Xi'an Jiaotong-Liverpool University, China

Submission guidelines: