Paper Type
ERF
Abstract
Information security (InfoSec) incidents, such as data breaches and privacy violations, are increasingly prevalent, posing significant societal risks. While media publications provide InfoSec advice to encourage protective behaviours among everyday users, users often fail to adopt these recommendations. This study investigates how language concreteness in InfoSec advice influences its effectiveness and the framing of fear appeals, drawing on construal level theory (CLT) and protection motivation theory (PMT). We hypothesize that concrete language enhances advice effectiveness (H1) and increases threat perception (H2). Using natural language processing (NLP) techniques, we will analyse a corpus of InfoSec advice articles from reputable sources (e.g., CISA, SANS, NIST) published between 2000 and 2024. The study aims to contribute to the security advice dissemination literature and provide practical guidance for crafting InfoSec messages that resonate with non-expert users. Findings will inform strategies to improve security advice dissemination and user compliance in an increasingly digital world.
Paper Number
2310
Recommended Citation
Lomo, Marvin Adjei Kojo, "Fear Appeal and Psychological Distance in InfoSec Advice" (2025). AMCIS 2025 Proceedings. 47.
https://aisel.aisnet.org/amcis2025/sig_sec/sig_sec/47
Fear Appeal and Psychological Distance in InfoSec Advice
Information security (InfoSec) incidents, such as data breaches and privacy violations, are increasingly prevalent, posing significant societal risks. While media publications provide InfoSec advice to encourage protective behaviours among everyday users, users often fail to adopt these recommendations. This study investigates how language concreteness in InfoSec advice influences its effectiveness and the framing of fear appeals, drawing on construal level theory (CLT) and protection motivation theory (PMT). We hypothesize that concrete language enhances advice effectiveness (H1) and increases threat perception (H2). Using natural language processing (NLP) techniques, we will analyse a corpus of InfoSec advice articles from reputable sources (e.g., CISA, SANS, NIST) published between 2000 and 2024. The study aims to contribute to the security advice dissemination literature and provide practical guidance for crafting InfoSec messages that resonate with non-expert users. Findings will inform strategies to improve security advice dissemination and user compliance in an increasingly digital world.
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SIGSEC