Applying Big Data Methods to Understanding Human Behavior and Health

• Published in: Frontiers in computational neuroscience Vol. 12; p. 84
• Main Authors: Moustafa, Ahmed A, Diallo, Thierno M O, Amoroso, Nicola, Zaki, Nazar, Hassan, Mubashir, Alashwal, Hany
• Format: Journal Article
• Language: English
• Published: Switzerland Frontiers Research Foundation 16.10.2018; Frontiers Media S.A
• Subjects: Algorithms; Alzheimer's disease; Artificial intelligence; Behavior; Big Data; Clustering; Data analysis; Data mining; Datasets; Deep learning; health; human behavior; Hypotheses; Machine learning; Medical imaging; Medical research; Neural networks; Neuroscience; Psychology; Researchers; Social networks; Social sciences; Statistical methods; Studies; Theory; Italy; Qatar; United Arab Emirates; deep learning; psychology; human behavior; health; big data; machine learning; causality; longitudinal data
• ISSN: 1662-5188; 1662-5188
• DOI: 10.3389/fncom.2018.00084

[...]most psychology researchers often collect data using a small number of variables to test their theory. [...]here we argue that it is good to let the data speak for themselves, that is, to take a data-driven approach. [...]a cluster is a collection of data points that are similar to one another and dissimilar to data points in other clusters (Escudero et al., 2011). [...]psychology researchers can benefit from these findings by focusing on improving scores on variables related to better academic performance.