How Do Like and Dislike Buttons Affect Communication? Testing the Privacy Calculus in a Preregistered One-Week Field Experiment

Abstract

According to the privacy calculus, both privacy concerns and expected gratifications explain self-disclosure online. So far, however, most findings were based on self-reports, and little is known about whether the privacy calculus can be used to explain observations of actual behavior. Likewise, we still know little as to whether the privacy calculus is influenced by the design of online websites, including for example popularity cues such as like and dislike buttons. To answer these questions, we ran a preregistered one-week field experiment. Participants were randomly distributed to three different websites, on which they discussed a current political topic. The websites featured either (a) like buttons, (b) like and dislike button, or (c) no like/dislike buttons, and were otherwise identical. The final sample consisted of 590 participants. Although the originally preregistered model was rejected, the results showed that a considerable share of actual self-disclosure could be explained by privacy concerns, gratifications, privacy deliberation, trust, and self-efficacy. The impact of the popularity cues on self-disclosure and the privacy calculus was negligible.

The Shorter the Better? Effects of Privacy Policy Length on Online Privacy Decision-Making

“…Participants who thought that privacy risks were likely did not disclose significantly less personal information. These results are contrary to the basic assumption of the privacy calculus and contradict the findings of a recent study that also collected behavioral data (Dienlin et al, 2019). Although plenty of studies have found support for the basic assumption of the privacy calculus (e.g., Bol et al, 2018;Dienlin & Metzger, 2016;Krasnova et al, 2009;Princi & Krämer, 2020), the approach is not without criticism (Knijnenburg et al, 2017).…”

“…To date, the privacy calculus has primarily been investigated in terms of behavioral intentions, and not the actual disclosure behaviors of individuals. A recent study, however, found that persons who had privacy concerns disclosed less information on an online discussion platform, whereas those who perceived disclosure to be beneficial actually disclosed more (Dienlin, Bräunlich, & Trepte, 2019). Hence, we also assume that the privacy calculus notions will hold with respect to actual behavior.…”

“…Although plenty of studies have found support for the basic assumption of the privacy calculus (e.g., Bol et al, 2018;Dienlin & Metzger, 2016;Krasnova et al, 2009;Princi & Krämer, 2020), the approach is not without criticism (Knijnenburg et al, 2017). The vast majority of pri-vacy calculus studies focused on intentions rather than on behavioral data (with the exception of the study by Dienlin et al, 2019). Hence, it may be that the privacy calculus holds in hypothetical decisions but not in concrete disclosure situations.…”

Self-disclosure on social networks: More than a rational decision-making process

“…However, it can be critically questioned whether individuals always deliberately weigh potential risks and benefits. Alongside, many studies focus on single relationships between risks/benefits and self-disclosure, which not concretely represents a weighing process (e.g., Dienlin et al, 2020;Knijnenburg et al, 2017). Further, previous studies demonstrated that benefits and risks/costs can impact self-disclosure intentions in different contexts (e.g., Bol et al, 2018;Krasnova et al, 2009), but a recent study found that only perceived benefits were significantly related to actual self-disclosures, while perceived risk likelihood was unrelated to participants' disclosure decisions .…”

Jenseits des Computational Turn: Methodenentwicklung und Forschungssoftware in der Kommunikations- und Medienwissenschaft – zur Einführung in das Themenheft

“…angepasst wird, dass sie für Forschung nutzbar wird. Einfache Beispiele dafür sind die Nutzung von Diskussionsplattformen mit Forumsarchitektur wie Discourse 13 für Online-Feldexperimente (Dienlin, Bräunlich & Trepte 2020) oder die Nutzung von Evernote als Tool zum Erstellen von Medientagebüchern (Koch et al 2019). Komplexere Beispiele finden sich im Bereich der digitalen Methoden, insbesondere bei der Digital Methods Initiative der Universität Amsterdam.…”