Pre-Conference Symposium: Big Data in Psychology 2019

Conference Archives

Pre-Conference Symposium: Big Data in Psychology 2019



May 27, 2019 – May 28, 2019

organized by the Leibniz Institute for Psychology Information (ZPID) at the
Center for Advanced Academic Studies (CAAS), Dubrovnik, Croatia

Associated special issue, to appear 2020 in Social Science Computer Review: Big Data in the Behavioral and Social Sciences.


Main conference, taking place May 29-31, 2019:
Research Synthesis 2019, http://researchsynthesis2019.leibniz-psychology.org

 

Registration is now closed.

 

(Please note that on this webpage you can only register for the “Big Data in Psychology Pre-Conference Symposium”.

If you wish to register for “Research Synthesis 2019 Conference” and also attend this Pre-Conference Symposium, please register through the main conference’s website here and make sure to check the box that signs you up for the “Big Data in Psychology Pre-Conference Symposium” in the online registration form, free of charge for participants of the main conference.)

 

Program schedule available here.

 

Full Program incl. additional useful information on psycharchives.org:

http://dx.doi.org/10.23668/psycharchives.2450


Abstract Collection available on psycharchives.org:

http://dx.doi.org/10.23668/psycharchives.2449

 

Aims and Scope of the Pre-Conference Symposium

The availability of Big Data is more and more common in many fields including business, computer science, government, social and behavioral sciences, and psychology. Since it is hard to clearly define what Big Data is, we do not impose a strict definition of Big Data in this pre-conference symposium.


There are three key characteristics that may qualify data as Big Data, namely Volume, Velocity, and Variety. High-volume data refers to the size of the dataset is too large that may lead to problems with storage and analysis. High-velocity data means that the data come at a high rate and/or have to be processed within a short period of time (e.g., real-time and interactive processing). High-variety data are data consisting of many types of structured and unstructured data with a mix of text, pictures, videos, and numbers. Another characteristic for Big Data is the veracity, which indicates the importance of the quality (or truthfulness) of data. Some examples of Big Data that may be relevant for Psychology are social media data, health/physiological tracker data, geolocation data, dynamic public records, travel route data, behavioral and genetic data. Papers submitted to this pre-conference symposium may focus on one or more of these features in Big Data.


The overall aim of this pre-conference symposium is to address methods and applications using Big Data in Psychology. The topics covered may address (but are not limited to):

  • Methodological and statistical issues in collecting, handling, processing, and analyzing Big Data in psychology.

  • Applications and illustrations of how Big Data are used to address psychological research questions.

  • Psychological interventions making use of Big Data.

  • Inference models taking Big Data into account.

  • Comparison of Big Data versus ´traditional´ data sources (e.g., self-reports, peer-reports, etc.).

  • Combining traditional data sources with Big Data.

  • Implications of Big Data for research infrastructures in psychology and related areas.


Invited Keynote Speakers

  • Ross Jacobucci, University of Notre Dame
    “Flexible Specification of Large Structural Equation Models with Regularization”

  • Joop Hox, Utrecht University
    "Big Data + Big Computers = Computational Psychology?"


Deadlines

Conference timeline

Special issue timeline
(Call for papers)

Dec 1, 2018

Structured abstracts due

Dec 31, 2018

Registration opens
Invitations to present due

Invitation to submit a full paper due

Jan 31, 2019

Registration of presenting authors due

Apr 15, 2019

Application grant due

Apr 30, 2019

Submission of conference presentations due

Full paper submission due

May 15, 2019

Registration closes

May 27-28, 2019

Big Data in Psychology Pre-Conference in Dubrovnik

Jul 15, 2019


Feedback to authors of full papers due

Aug 15, 2019

Revised manuscripts due

Aug 31, 2019

Editorial decision about acceptance or refusal of revised papers due

2020

Publication of special issue


Full Program incl. additional useful information on psycharchives.org:

http://dx.doi.org/10.23668/psycharchives.2450

 

Abstract Collection available on psycharchives.org:

 

http://dx.doi.org/10.23668/psycharchives.2449

Registration fees for Pre-Conference Symposium Big Data in Psychology ONLY:

Non-presenting participants (from Dec 31, 2018):
EUR 100.-


Presenters (from Dec 31, 2018):
EUR 50.-

*special offer* closed - deadlinie has ended

Grant for 10 PhD or master students - For conditions and details see webpage "Research Synthesis 2019 Conference" - Deadline for applications: April 15, 2019 *Please do not apply as the deadline has ended*

View Conference Details

Big Data in Psychology 2018



Trier, DE

June 7, 2018 – June 9, 2018

Leibniz Institute for Psychology Information (ZPID)

Event location: University of Trier, Campus II - Kapelle (Please note that the university has two different campuses, we are at the second one!)

 

The availability of Big Data is more and more common in many fields including business, computer science, government, social and behavioral sciences, and psychology. Since it is hard to clearly define what Big Data is, we do not impose a strict definition of Big Data in this conference.

There are three key characteristics that may qualify data as Big Data, namely Volume, Velocity, and Variety. High-volume data refers to the size of the dataset is too large that may lead to problems with storage and analysis. High-velocity data means that the data come at a high rate and/or have to be processed within a short period of time (e.g., real-time and interactive processing). High-variety data are data consisting of many types of structured and unstructured data with a mix of text, pictures, videos, and numbers. Another characteristic for Big Data is the veracity, which indicates the importance of the quality (or truthfulness) of data. Some examples of Big Data that may be relevant for Psychology are social media data, health/physiological tracker data, geolocation data, dynamic public records, travel route data, behavioral and genetic data. Papers submitted to this conference may focus on one or more of these features in Big Data.

The overall aim of this conference is to address methods and applications using Big Data in Psychology. The topics covered may address (but are not limited to):
  • Methodological and statistical issues in collecting, handling, processing, and analyzing Big Data in psychology.
  • Applications and illustrations of how Big Data are used to address psychological research questions.
  • Psychological interventions making use of Big Data.
  • Inference models taking Big Data into account.
  • Comparison of Big Data versus ´traditional´ data sources (e.g., self-reports, peer-reports, etc.).
  • Combining traditional data sources with Big Data.
  • Implications of Big Data for research infrastructures in psychology and related areas.

 

Invited Keynote Speakers

Mike Cheung, National University of Singapore:
"Testing model driven hypotheses with Big Data."

Katrijn van Deun, Tilburg University:
"Big Data in Psychology: Statistical methods for linked high-dimensional with traditional data."

Andreas Brandmaier, Max Planck Institute for Human Development:
"The best of both worlds: Towards a synthesis of theory-based and data-driven modeling."

Michael Neale, Virginia Commonwealth University:
"Structural Equation Modeling of Big Data: Challenges and Opportunities."

Fred Oswald, Rice University:
"The Hype, Reality, and Hope for Big Data Analyses in Psychological Research."


The final program is now available!

To view the final program of the conference, click here.

Please find the abstract collection for all planned sessions here.

For the final program of the associated conference Research Synthesis (June 10-12, 2018), click here.

An associated conference on hotspot topics in subfields and related fields of Psychology and their exploration through research synthesis methods will take place at ZPID - Leibniz Institute for Psychology Information in Trier, Germany, on June 10-12, 2018. For further details, click here.


“Ad hoc” childcare for conference participants and presenters

We have arranged for free childcare service for accompanying children of participants and presenters attending the “Big Data in Psychology” (June, 7-9, 2018) and/or “Research Synthesis” (June, 10-12, 2018) conference. During the conference hours, qualified care of the children will be provided by employees of the Caritas family services. Childcare is located at University of Trier, Campus I (student residence building IV; “ad hoc-Raum für Kinder”), about 10-15 minutes from the conference venue (walking distance).
To sign up for this free service send an e-mail (events@leibniz-psychology.org) with your name and the number of children who will attend. Any questions that may arise can be directed to the same e-mail address.

 

Registration fee

Early Bird (Dec 15 until Apr 15): EUR 250.-

Regular (Apr 16 until May 15): EUR 300.-

Late (May 16 until June 7): EUR 350.-

(Please note that there is a reduced registration fee option if you are presenting at this conference.)

View Conference Details



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