2020
DOI: 10.1002/arcp.1063
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Habits and the electronic herd: The psychology behind social media’s successes and failures

Abstract: If platforms such as Facebook, Instagram, and Twitter are the engines of social media use, what is the gasoline? The answer can be found in the psychological dynamics behind consumer habit formation and performance. In fact, the financial success of different social media sites is closely tied to the daily‐use habits they create among users. We explain how the rewards of social media sites motivate user habit formation, how social media design provides cues that automatically activate habits and nudge continue… Show more

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Cited by 71 publications
(86 citation statements)
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References 83 publications
(118 reference statements)
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“…Future research should combine user-centered self-reports with technology-centered logging data (e.g., Aalbers et al, 2021), which would reduce the threat of common method bias present in this study. While this study’s habit measure (SRBAI) is well-established (Bayer & LaRose, 2018; Gardner et al, 2012; Wood & Rünger, 2016), future research could leverage implicit response-frequency measures of habit strength (Naab & Schnauber, 2016) or use experimental designs that, for instance, vary the amount of social or technical cues (Anderson & Wood, 2021; Bayer, Campbell et al, 2016).…”
Section: Discussionmentioning
confidence: 99%
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“…Future research should combine user-centered self-reports with technology-centered logging data (e.g., Aalbers et al, 2021), which would reduce the threat of common method bias present in this study. While this study’s habit measure (SRBAI) is well-established (Bayer & LaRose, 2018; Gardner et al, 2012; Wood & Rünger, 2016), future research could leverage implicit response-frequency measures of habit strength (Naab & Schnauber, 2016) or use experimental designs that, for instance, vary the amount of social or technical cues (Anderson & Wood, 2021; Bayer, Campbell et al, 2016).…”
Section: Discussionmentioning
confidence: 99%
“…For instance, experience sampling studies could combine descriptive screen time measures (i.e., behavioral frequency) and frequency-independent automaticity measures at multiple levels of mobile social media use (e.g., for various devices, applications, and features; Meier & Reinecke, 2020). This would allow assessments of their relative impact on well-being: it may help identify which device-, application-, or feature-specific habits (Anderson & Wood, 2021) and usage contexts pose the biggest challenges to maintain a healthy balance between connection and disconnection (Vanden Abeele, 2020). Such designs could be combined with experimental tests of digital well-being interventions (e.g., apps), which represent increasingly popular but largely untested “tech solutions to tech problems” (Bayer & LaRose, 2018, p. 122).…”
Section: Discussionmentioning
confidence: 99%
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“…The cues provided by social networking applications through sophisticated algorithms, which determine the receipt of notifications and page layout, as well as individual (e.g., mood) and contextual (e.g., commuting time) factors, facilitate a habitual use of the smartphone. Repeatedly used applications like social media and instant messaging platforms 65 foster the experience of short-term gratifications from incoming notifications, messages, and Likes, to the point that motivations for smartphone use are substituted by habitual use 70 . In fact, according to a recent scoping review on neuroscientific studies, online activities produce strong rewards for the brain, thus fostering subsequent use to seek short-term gratifications 71 .…”
Section: Discussionmentioning
confidence: 99%