Cemiloglu D., Naiseh M., Catania M., Oinas-Kukkonen H., Ali R. (2021) The Fine Line Between Persuasion and Digital Addiction. In: Ali R., Lugrin B., Charles F. (eds) Persuasive Technology. PERSUASIVE 2021. Lecture Notes in Computer Science, vol 12684. Springer, Cham. https://doi.org/10.1007/978-3-030-79460-6_23
The fine line between persuasion and digital addiction
|Author:||Cemiloglu, Deniz1; Naiseh, Mohammad1; Catania, Maris2;|
1Faculty of Science and Technology, Bournemouth University, Poole, UK
2Kindred Group, Sliema, Malta
3Oulu Advanced Research on Service and Information Systems, University of Oulu, Finland
4College of Science and Engineering, Hamad Bin Khalifa University, Qatar
|Online Access:||PDF Full Text (PDF, 0.3 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe2021092847274
|Publish Date:|| 2021-09-28
Digital addiction is becoming a prevalent societal concern and persuasive design techniques used in digital platforms might be accountable also for the development and maintenance of such problematic behavior. This paper theoretically analyses the relationship between persuasive system design principles and digital addiction in light of theories on behavioral and substance-based addictions. The findings suggest that some of the persuasive design principles, in specific contexts, may trigger and expedite digital addiction. The purpose of this paper is to open a discussion around the potential effects of persuasive technology on digital addiction and cater to this risk in the design processes and the persuasive design itself.
Lecture notes in computer science
|Pages:||289 - 307|
|Type of Publication:||
A3 Book chapter
|Field of Science:||
113 Computer and information sciences
This work has been partly supported by Kindred Group – Division of Responsible Gaming and Research, through a match-funded PhD project titled “Responsibility by Design: the Case of Online Gambling”.
© Springer Nature Switzerland AG 2021. This is a post-peer-review, pre-copyedit version of an article published in Lecture Notes in Computer Science. The final authenticated version is available online at:https://doi.org/10.1007/978-3-030-79460-6_23.