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Meeting Strangers Online: Feature Models for Trustworthiness Assessment
Publikationstyp
Conference Paper
Date Issued
2022-08
Sprache
English
Institut
First published in
Number in series
13482 LNCS
Start Page
3
End Page
22
Citation
9th IFIP WG 13.2 International Working Conference on Human-Centered Software Engineering (HCSE 2022)
Contribution to Conference
Publisher DOI
Scopus ID
Getting to know new people online to later meet them offline for neighbourhood help, carpooling, or online dating has never been as easy as nowadays by social media performing computer-mediated introductions (CMIs). Unfortunately, interacting with strangers poses high risks such as unfulfilled expectations, fraud, or assaults. People most often tolerate risks if they believe others are trustworthy. However, conducting an online trustworthiness assessment usually is a challenge. Online cues differ from offline ones and people are either lacking awareness for the assessment’s relevance or find it too complicated. On these grounds, this work aims to aid software engineers to develop CMI that supports users in their online trustworthiness assessment. We focus on trust-related software features and nudges to i) increase user awareness, ii) trigger the trustworthiness assessment and iii) enable the assessment online. For that reason, we extend feature models to provide software engineers the possibility to create and document software features or nudges for trustworthiness assessment. The extended feature models for trustworthiness assessments can serve as reusable catalogues for validating features in terms of their impact on the trustworthiness assessment and for configuring CMI software product lines. Moreover, this work provides an example of how the extended feature models can be applied to catfishing protection in online dating.
Subjects
Feature models
Nudging
Social media
Trustworthiness
User-centred design