Finding the traces of behavioral and cognitive processes in big data and naturally occurring datasets.

Today, people generate and store more data than ever before as they interact with both real and virtual environments. These digital traces of behavior and cognition offer cognitive scientists and psychologists an unprecedented opportunity to test theories outside the laboratory. Despite general excitement about big data and naturally occurring datasets among researchers, three gaps stand in the way of their wider adoption in theory-driven research: the imagination gap, the skills gap, and the culture gap. We outline an approach to bridging these three gaps while respecting our responsibilities to the public as participants in and consumers of the resulting research. To that end, we introduce Data on the Mind ( http://www.dataonthemind.org ), a community-focused initiative aimed at meeting the unprecedented challenges and opportunities of theory-driven research with big data and naturally occurring datasets. We argue that big data and naturally occurring datasets are most powerfully used to supplement-not supplant-traditional experimental paradigms in order to understand human behavior and cognition, and we highlight emerging ethical issues related to the collection, sharing, and use of these powerful datasets

Reception of subjectivity of critical theory and Machiavellianism : a proposal for computer aided diagnosis of pathology in education

The authors of this paper, while observing the Polish education system, can not accept the ossified administrative structures existing in the system and the triumph of economic objectives over the human ones, the latter understood as individuals having the opportunity for self-realisation (developing one's subjectivity). We want to ask what identities an education system functioning in this way would create? A lot of attention is devoted in the literature to the problem of education. We also want to speak on this matter, for the sake of the common good which education undoubtedly is. We sincerely hope that the perception of problems in the system will lead to its repair and not its destruction. This paper consists of two main parts. The first part presents the reconstruction of critical theory based on the philosophy of Theodor Adorno, Max Horkheimer and Jurgen Habermas, which concerns the concept of subjectivity. The notion of subjectivity emerging from the thoughts of the representatives of the Frankfurt School is then confronted with the image of man created by the Machiavellian thought, according to social sciences. This is followed by a description of the Machiavellian personality trait, based on the psychological interpretation of Machiavellianism, and not on the current philosophical interpretation. In the second part, the authors present the proposal for using computer exploration methods to identify Machiavellian behaviours. The proposed solution takes into account cognitive, educational and preventive aspects

Discovering Predictive Event Sequences in Criminal Careers

In this work, we consider the problem of predicting criminal behavior, and propose a method for discovering predictive patterns in criminal histories. Quantitative criminal career analysis typically involves clustering individuals according to frequency of a particular event type over time, using cluster membership as a basis for comparison. We demonstrate the effectiveness of hazard pattern mining for the discovery of relationships between different types of events that may occur in criminal careers. Hazard pattern mining is an extension of event sequence mining, with the additional restriction that each event in the pattern is the first subsequent event of the specified type. This restriction facilitates application of established time based measures such as those used in survival analysis. We evaluate hazard patterns using a relative risk model and an accelerated failure time model. The results show that hazard patterns can reliably capture unexpected relationships between events of different types

Contemporary approaches to modelling the consumer

Modelling is an exciting area of consumer psychology, with application to many problems and contexts. We have covered the founding principles and objectives of the modelling process, which have remained largely unchanged over the course of time. What has changed are the constant innovations in methodologies (especially analyses) and software development that keep pushing the boundaries of modelling. These developments have given rise to some interesting opportunities to work in multidisciplinary teams (especially around exploiting big data in a meaningful way) and to the opening up of new and innovative areas of research in understanding the consumer

Element-centric clustering comparison unifies overlaps and hierarchy

Clustering is one of the most universal approaches for understanding complex data. A pivotal aspect of clustering analysis is quantitatively comparing clusterings; clustering comparison is the basis for many tasks such as clustering evaluation, consensus clustering, and tracking the temporal evolution of clusters. In particular, the extrinsic evaluation of clustering methods requires comparing the uncovered clusterings to planted clusterings or known metadata. Yet, as we demonstrate, existing clustering comparison measures have critical biases which undermine their usefulness, and no measure accommodates both overlapping and hierarchical clusterings. Here we unify the comparison of disjoint, overlapping, and hierarchically structured clusterings by proposing a new element-centric framework: elements are compared based on the relationships induced by the cluster structure, as opposed to the traditional cluster-centric philosophy. We demonstrate that, in contrast to standard clustering similarity measures, our framework does not suffer from critical biases and naturally provides unique insights into how the clusterings differ. We illustrate the strengths of our framework by revealing new insights into the organization of clusters in two applications: the improved classification of schizophrenia based on the overlapping and hierarchical community structure of fMRI brain networks, and the disentanglement of various social homophily factors in Facebook social networks. The universality of clustering suggests far-reaching impact of our framework throughout all areas of science

Human Lesion Studies in the 21st Century

The study of patients with brain lesions has made major historical contributions to cognitive neuroscience. Here I argue for an increased investment in modern lesion mapping, complementing fMRI studies and laying the conceptual and analytic foundations for future techniques that could experimentally manipulate human brain function