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This study aims to extend and explore patterns and trends of research in the linkage of big data and knowledge management (KM) by identifying growth in terms of numbers of papers and current and emerging themes and to propose areas of future research.

The study was conducted by systematically extracting, analysing and synthesizing the literature related to linkage between big data and KM published in top-tier journals in Web of Science (WOS) and Scopus databases by exploiting bibliometric techniques along with theory, context, characteristics, methodology (TCCM) analysis.

The study unfolds four major themes of linkage between big data and KM research, namely (1) conceptual understanding of big data as an enabler for KM, (2) big data–based models and frameworks for KM, (3) big data as a predictor variable in KM context and (4) big data applications and capabilities. It also highlights TCCM of big data and KM research through which it integrates a few previously reported themes and suggests some new themes.

This study extends advances in the previous reviews by adding a new time line, identifying new themes and helping in the understanding of complex and emerging field of linkage between big data and KM. The study outlines a holistic view of the research area and suggests future directions for flourishing in this research area.

This study highlights the role of big data in KM context resulting in enhancement of organizational performance and efficiency. A summary of existing literature and future avenues in this direction will help, guide and motivate managers to think beyond traditional data and incorporate big data into organizational knowledge infrastructure in order to get competitive advantage.

To the best of authors’ knowledge, the present study is the first study to go deeper into understanding of big data and KM research using bibliometric and TCCM analysis and thus adds a new theoretical perspective to existing literature.

This paper aims to explore advances in indirect personality assessment, with emphasis on the psychology of digital behavior based on the analysis of new technological devices and platforms for interpersonal relationships, identifying – along the way – those findings that may be useful to carry out a reconstructive psychological assessment (RPA) of applicability in the legal context.

Different fields of knowledge are explored, transferring the findings to the field of psychology of digital behavior, analyzing the publications that report findings on the analysis of new technological devices and platforms for interpersonal relationships and identifying – along the way – those findings that may result useful to carry out an RPA of applicability in the legal context.

The application of RPA represents a significant advance in the integration of criminal psychology and forensic technology in legal contexts, opening new fields of action for forensic psychology.

The article has transferred advances in computer science to the field of forensic psychology, with emphasis on the relevance of RPA (from the analysis of digital behavioral residues) in the interpretation of behavioral evidence for the indirect evaluation of the personality and within the judicial context (when the victim and/or accused are not included).