Facebook is rapidly gaining recognition as a powerful research tool for the social sciences. It constitutes a large and diverse pool of participants, who can be selectively recruited for both online and offline studies. Additionally, it facilitates data collection by storing detailed records of its users' demographic profiles, social interactions, and behaviors. With participants' consent, these data can be recorded retrospectively in a convenient, accurate, and inexpensive way. Based on our experience in designing, implementing, and maintaining multiple Facebook-based psychological studies that attracted over 10 million participants, we demonstrate how to recruit participants using Facebook, incentivize them effectively, and maximize their engagement. We also outline the most important opportunities and challenges associated with using Facebook for research, provide several practical guidelines on how to successfully implement studies on Facebook, and finally, discuss ethical considerations.
SignificanceBuilding on recent advancements in the assessment of psychological traits from digital footprints, this paper demonstrates the effectiveness of psychological mass persuasion—that is, the adaptation of persuasive appeals to the psychological characteristics of large groups of individuals with the goal of influencing their behavior. On the one hand, this form of psychological mass persuasion could be used to help people make better decisions and lead healthier and happier lives. On the other hand, it could be used to covertly exploit weaknesses in their character and persuade them to take action against their own best interest, highlighting the potential need for policy interventions.
Background: Recent trends on measurement of well-being have elevated the scientific standards and rigor associated with approaches for national and international comparisons of well-being. One major theme in this has been the shift toward multidimensional approaches over reliance on traditional metrics such as single measures (e.g. happiness, life satisfaction) or economic proxies (e.g. GDP). Methods: To produce a cohesive, multidimensional measure of well-being useful for providing meaningful insights for policy, we use data from 2006 and 2012 from the European Social Survey (ESS) to analyze well-being for 21 countries, involving approximately 40,000 individuals for each year. We refer collectively to the items used in the survey as multidimensional psychological well-being (MPWB). Results: The ten dimensions assessed are used to compute a single value standardized to the population, which supports broad assessment and comparison. It also increases the possibility of exploring individual dimensions of well-being useful for targeting interventions. Insights demonstrate what may be masked when limiting to single dimensions, which can create a failure to identify levers for policy interventions. Conclusions: We conclude that both the composite score and individual dimensions from this approach constitute valuable levels of analyses for exploring appropriate policies to protect and improve well-being.
In contrast to decades of research reporting surprisingly weak relationships between consumption and happiness, recent findings suggest that money can indeed increase happiness if it is spent the "right way" (e.g., on experiences or on other people). Drawing on the concept of psychological fit, we extend this research by arguing that individual differences play a central role in determining the "right" type of spending to increase well-being. In a field study using more than 76,000 bank-transaction records, we found that individuals spend more on products that match their personality, and that people whose purchases better match their personality report higher levels of life satisfaction. This effect of psychological fit on happiness was stronger than the effect of individuals' total income or the effect of their total spending. A follow-up study showed a causal effect: Personality-matched spending increased positive affect. In summary, when spending matches the buyer's personality, it appears that money can indeed buy happiness.
The automatic assessment of psychological traits from digital footprints allows researchers to study psychological traits at unprecedented scale and in settings of high ecological validity. In this research, we investigated whether spending records—a ubiquitous and universal form of digital footprint—can be used to infer psychological traits. We applied an ensemble machine-learning technique ( random-forest modeling) to a data set combining two million spending records from bank accounts with survey responses from the account holders ( N = 2,193). Our predictive accuracies were modest for the Big Five personality traits ( r = .15, corrected ρ = .21) but provided higher precision for specific traits, including materialism ( r = .33, corrected ρ = .42). We compared the predictive accuracy of these models with the predictive accuracy of alternative digital behaviors used in past research, including those observed on social media platforms, and we found that the predictive accuracies were relatively stable across socioeconomic groups and over time.
People actively select their environments, and the environments they select can alter their psychological characteristics in the moment and over time. Such dynamic person–environment transactions are likely to play out in the context of daily life via the places people spend time in (e.g., home, work, or public places like cafes and restaurants). This article investigates personality–place transactions at 3 conceptual levels: stable personality traits, momentary personality states, and short-term personality trait expressions. Three 2-week experience sampling studies (2 exploratory and 1 confirmatory with a total N = 2,350 and more than 63,000 momentary assessments) were used to provide the first large-scale evidence showing that people’s stable Big Five traits are associated with the frequency with which they visit different places on a daily basis. For example, extraverted people reported spending less time at home and more time at cafés, bars, and friends’ houses. The findings also show that spending time in a particular place predicts people’s momentary personality states and their short-term trait expression over time. For example, people reported feeling more extraverted in the moment when spending time at bars/parties, cafés/restaurants, or friends’ houses, compared with when at home. People who showed preferences for spending more time in these places also showed higher levels of short-term trait extraversion over the course of 2 weeks. The findings make theoretical contributions to environmental psychology, personality dynamics, as well as the person–environment transactions literature, and highlight practical implications for a world in which the places people visit can be easily captured via GPS sensors.
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