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Cuartas Arias, J. M. (2017). Big data for use in psychological research. International Journal of Psychological Research, 10(1), 6–7. https://doi.org/10.21500/20112084.2828
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To give up copyright, the authors allow that, International Journal of Psychological Research, distribute the work more broadly, check for the reuse by others and take care of the necessary procedures for the registration and administration of copyright; at the same time, our editorial board represents the interests of the author and allows authors to re-use his work in various forms. In response to the above, authors transfer copyright to the journal, International Journal of Psychological Research. This transfer does not imply other rights which are not those of authorship (for example those that concern about patents). Likewise, preserves the authors rights to use the work integral or partially in lectures, books and courses, as well as make copies for educational purposes. Finally, the authors may use freely the tables and figures in its future work, wherever make explicit reference to the previous publication in International Journal of Psychological Research. The assignment of copyright includes both virtual rights and forms of the article to allow the editorial to disseminate the work in the manner which it deems appropriate.
The editorial board reserves the right of amendments deemed necessary in the application of the rules of publication.
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References
Chen, E. E., & Wojcik, S. P. (2016). A practical guide to big
data research in psychology [Journal Article]. Psychol
Methods, 21(4), 458-474. doi: 10.1037/met0000111
eMarketer. (2017). Home to research and data on nearly
every digital topic (No. January 5th 2017). Retrieved
from https://www.emarketer.com/
Kern, M. L., Eichstaedt, J., Schwartz, H. A., Park, G., Ungar,
L. H., Stillwell, D. J., . . . Seligman, M. E. (2014).
From ”sooo excited!!!” to ”so proud”: using language
to study development. Dev Psychol, 50(1), 178-88. doi:
10.1037/a0035048
Kosinski, M., Wang, Y., Lakkaraju, H., & Leskovec, J. (2016).
Mining big data to extract patterns and predict reallife
outcomes. Psychol Methods, 21(4), 493-506. doi:
10.1037/met0000105
Markowetz, A., Blaszkiewicz, K., Montag, C., Switala, C.,
& Schlaepfer, T. E. (2014). Psycho-informatics: Big
data shaping modern psychometrics. Med Hypotheses,
82(4), 405-411. doi: 016/j.mehy.2013.11.030
data research in psychology [Journal Article]. Psychol
Methods, 21(4), 458-474. doi: 10.1037/met0000111
eMarketer. (2017). Home to research and data on nearly
every digital topic (No. January 5th 2017). Retrieved
from https://www.emarketer.com/
Kern, M. L., Eichstaedt, J., Schwartz, H. A., Park, G., Ungar,
L. H., Stillwell, D. J., . . . Seligman, M. E. (2014).
From ”sooo excited!!!” to ”so proud”: using language
to study development. Dev Psychol, 50(1), 178-88. doi:
10.1037/a0035048
Kosinski, M., Wang, Y., Lakkaraju, H., & Leskovec, J. (2016).
Mining big data to extract patterns and predict reallife
outcomes. Psychol Methods, 21(4), 493-506. doi:
10.1037/met0000105
Markowetz, A., Blaszkiewicz, K., Montag, C., Switala, C.,
& Schlaepfer, T. E. (2014). Psycho-informatics: Big
data shaping modern psychometrics. Med Hypotheses,
82(4), 405-411. doi: 016/j.mehy.2013.11.030
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