Human and Computer Personality Prediction From Digital Footprints

Abstract

Is it possible to judge someone accurately from his or her online activity? The Internet provides vast opportunities for individuals to present themselves in different ways, from simple self-enhancement to malicious identity fraud. We often rely on our Internet-based judgments of others to make decisions, such as whom to socialize with, date, or employ. Recently, personality-perception researchers have turned to studying social media and digital devices in order to ask whether a person's digital traces can reveal aspects of his or her identity. Simultaneously, advances in "big data" analytics have demonstrated that computer algorithms can predict individuals' traits from their digital traces. In this article, we address three questions: What do we currently know about human-and computer-based personality assessments? How accurate are these assessments? Where are these fields heading? We discuss trends in the current findings, provide an overview of methodological approaches, and recommend directions for future research.

Open source smartphone app and tools for measuring, quantifying, and visualizing technology use

“…This typically relies on asking a person for a duration estimate or a qualitative reflection concerning their own experience rather than objectively measuring behavior from a device (Ellis, 2019)1. While such measurements are typical across social psychology, it remains problematic when attempting to describe behaviors or understand related psychological impacts (Baumeister, Vohs, & Funder, 2007;Doliński, 2018;Hinds & Joinson, 2019;Sassenberg, & Ditrich, 2019). It is generally accepted that single duration estimates will not explain the range of experiences provided by modern technology (Boas, & Ling, 2013;Ellis et al, 2019) and survey instruments poorly correlate with a variety of behaviors, especially those which are automatic or habitual (e.g., smartphone checks) (Andrews, Ellis, Shaw, & Piwek, 2015;Ellis, Davidson, Shaw, & Geyer, 2018;Ellis, 2019).…”

Public attitudes towards algorithmic personalization and use of personal data online: Evidence from Germany, Great Britain, and the United States

“…Further concerns relate to data privacy and transparency: People's data are at the heart of the online ecosystem, where service providers monetize behavioral traces collected directly or by third-party trackers (9). This widespread collection of behavioral data permits AI algorithms to infer more information than people intend to share (e.g., information on sexual orientation, personality traits, and political views; [10][11][12][13][14]. But how aware are people of these processes?…”

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“…Накопленный на втором этапе массив данных, касающийся взаимосвязей «цифровой» личности с поведением человека в реальной жизни, позволит перейти к третьему этапу -проверке точности прогнозирования и применению выявленных закономерностей на практике. Хотя пока нарисованная картина выглядит не совсем реальной, однако все больше специалистов допускают подобное развитие ситуации в этой научной области Hinds, Joinson, 2019).…”