What Technology and Big Data Can Do for Social and Personality Psychology

2014 ◽  
Author(s):  
Jean-Baptiste Michel
Keyword(s):  
Big Data ◽  
Personality Psychology

scholarly journals The Personality Panorama: Conceptualizing Personality through Big Behavioural Data

2020 ◽  
Vol 34 (5) ◽  
pp. 599-612 ◽  
Author(s):  
Ryan L. Boyd ◽  
Paola Pasca ◽  
Kevin Lanning
Keyword(s):  
Big Data ◽  
New Technologies ◽  
Historical Thinking ◽  
Self Report ◽  
Ethical Considerations ◽  
Personality Psychology ◽  
The Public ◽  
New Methods ◽  
Behavioural Assessment ◽  
The Face

Personality psychology has long been grounded in data typologies, particularly in the delineation of behavioural, life outcome, informant–report, and self–report sources of data from one another. Such data typologies are becoming obsolete in the face of new methods, technologies, and data philosophies. In this article, we discuss personality psychology's historical thinking about data, modern data theory's place in personality psychology, and several qualities of big data that urge a rethinking of personality itself. We call for a move away from self–report questionnaires and a reprioritization of the study of behaviour within personality science. With big data and behavioural assessment, we have the potential to witness the confluence of situated, seamlessly interacting psychological processes, forming an inclusive, dynamic, multiangle view of personality. However, big behavioural data come hand in hand with important ethical considerations, and our emerging ability to create a ‘personality panopticon’ requires careful and thoughtful navigation. For our research to improve and thrive in partnership with new technologies, we must not only wield our new tools thoughtfully, but humanely. Through discourse and collaboration with other disciplines and the general public, we can foster mutual growth and ensure that humanity's burgeoning technological capabilities serve, rather than control, the public interest. © 2020 European Association of Personality Psychology

Using Big Data and Machine Learning in Personality Measurement: Opportunities and Challenges

2020 ◽  
Vol 34 (5) ◽  
pp. 632-648
Author(s):  
Leo Alexander ◽  
Evan Mulfinger ◽  
Frederick L. Oswald
Keyword(s):  
Machine Learning ◽  
Big Data ◽  
European Association ◽  
Reliability And Validity ◽  
Personality Measurement ◽  
Personality Psychology ◽  
Personality Research ◽  
The Future ◽  
Challenges And Opportunities ◽  
Conceptual Paper

This conceptual paper examines the promises and critical challenges posed by contemporary personality measurement using big data. More specifically, the paper provides (i) an introduction to the type of technologies that give rise to big data, (ii) an overview of how big data is used in personality research and how it might be used in the future, (iii) a framework for approaching big data in personality science, (iv) an exploration of ideas that connect psychometric reliability and validity, as well as principles of fairness and privacy, to measures of personality that use big data, (v) a discussion emphasizing the importance of collaboration with other disciplines for personality psychologists seeking to adopt big data methods, and finally, (vi) a list of practical considerations for researchers seeking to move forward with big data personality measurement and research. It is expected that this paper will provide insights, guidance, and inspiration that helps personality researchers navigate the challenges and opportunities posed by using big data methods in personality measurement. © 2020 European Association of Personality Psychology

Tracking Fluctuations in Psychological States using Social Media Language: A Case Study of Weekly Emotion

2020 ◽  
Vol 34 (5) ◽  
pp. 845-858
Author(s):  
Johannes C. Eichstaedt ◽  
Aaron C. Weidman
Keyword(s):  
Big Data ◽  
Big Five ◽  
Emotional Valence ◽  
Data Set ◽  
Personality Psychology ◽  
Aggregated Data ◽  
Psychological States ◽  
Final Data ◽  
Valence And Arousal

Personality psychologists are increasingly documenting dynamic, within–person processes. Big data methodologies can augment this endeavour by allowing for the collection of naturalistic and personality–relevant digital traces from online environments. Whereas big data methods have primarily been used to catalogue static personality dimensions, here we present a case study in how they can be used to track dynamic fluctuations in psychological states. We apply a text–based, machine learning prediction model to Facebook status updates to compute weekly trajectories of emotional valence and arousal. We train this model on 2895 human–annotated Facebook statuses and apply the resulting model to 303 575 Facebook statuses posted by 640 US Facebook users who had previously self–reported their Big Five traits, yielding an average of 28 weekly estimates per user. We examine the correlations between model–predicted emotion and self–reported personality, providing a test of the robustness of these links when using weekly aggregated data, rather than momentary data as in prior work. We further present dynamic visualizations of weekly valence and arousal for every user, while making the final data set of 17 937 weeks openly available. We discuss the strengths and drawbacks of this method in the context of personality psychology's evolution into a dynamic science. © 2020 European Association of Personality Psychology

Bringing Back the Person into Behavioural Personality Science Using Big Data

2020 ◽  
Vol 34 (5) ◽  
pp. 670-686
Author(s):  
Karl–Heinz Renner ◽  
Stephanie Klee ◽  
Timo von Oertzen
Keyword(s):  
Big Data ◽  
Literature Review ◽  
New Technologies ◽  
Research Topics ◽  
Personality Psychology ◽  
Individual Person ◽  
New Methods ◽  
Data Collection And Analysis ◽  
History Of ◽  
The Individual

Behaviour and the individual person are important but widely neglected topics of personality psychology. We argue that new technologies to collect and new methods to analyse Big (Behavioural) Data have the potential to bring back both more behaviour and the individual person into personality science. The call for studying the individual person in the history of personality science, the related idiographic/nomothetic divide, as well as attempts to reconcile these two approaches are briefly reviewed. Furthermore, different meanings of the term idiographic and some unique selling points that emphasize the importance of idiographic research are highlighted. A nonexhaustive literature review shows that a wealth of behaviours are considered in extant personality studies using such Big Data but only in a nomothetic way. Against this background, we demonstrate the potential of Big Data collection and analysis with regard to four idiographic research topics: (i) unique manifestations of common traits and the resurgence of personal dispositions, (ii) idiographic prediction, (iii) intraindividual consistency versus variability of behaviour and (iv) intraindividual personality trait change through intervention. Methodological, ethical and legal pitfalls of doing Big Data research with individual persons as well as potential countermeasures are considered.

Find Out About 'Big Data' to Track Outcomes

ASHA Leader ◽  
2013 ◽  
Vol 18 (2) ◽  
pp. 59-59
Keyword(s):  
Big Data

Find Out About 'Big Data' to Track Outcomes

Correlating Personality and Actual Phone Usage

2014 ◽  
Vol 35 (3) ◽  
pp. 158-165 ◽  
Author(s):  
Christian Montag ◽  
Konrad Błaszkiewicz ◽  
Bernd Lachmann ◽  
Ionut Andone ◽  
Rayna Sariyska ◽  
...  
Keyword(s):  
Big Data ◽  
Social Network ◽  
Mobile Phone ◽  
Mobile Phones ◽  
Self Report ◽  
Psychological Variables ◽  
New Approach ◽  
Report Data ◽  
Self Report Data ◽  
Voice Calls

In the present study we link self-report-data on personality to behavior recorded on the mobile phone. This new approach from Psychoinformatics collects data from humans in everyday life. It demonstrates the fruitful collaboration between psychology and computer science, combining Big Data with psychological variables. Given the large number of variables, which can be tracked on a smartphone, the present study focuses on the traditional features of mobile phones – namely incoming and outgoing calls and SMS. We observed N = 49 participants with respect to the telephone/SMS usage via our custom developed mobile phone app for 5 weeks. Extraversion was positively associated with nearly all related telephone call variables. In particular, Extraverts directly reach out to their social network via voice calls.

“Big Data in Psychology: Methods and Applications”

2017 ◽  
Vol 225 (3) ◽  
pp. 287-288
Keyword(s):  
Big Data

An associated conference will take place at ZPID – Leibniz Institute for Psychology Information in Trier, Germany, on June 7–9, 2018. For further details, see: http://bigdata2018.leibniz-psychology.org

Traits and trade-offs are insufficient for evolutionary personality psychology.

2007 ◽  
Vol 62 (9) ◽  
pp. 1073-1074 ◽  
Author(s):  
Kennon M. Sheldon ◽  
Melanie S. Sheldon ◽  
Charles P. Nichols
Keyword(s):  
Personality Psychology ◽  
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