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Meeting Strangers Online: Feature Models for Trustworthiness Assessment

Angela Borchert ; Nicolás E. Díaz Ferreyra ; Maritta Heisel (2022) — Human-Centered Software Engineering (HCSE 2022), LNCS 13482

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DOI: 10.1007/978-3-031-14785-2_1 (opens in a new tab)

Country:   Global
Tags:   Catfishing, Digital Nudges, Feature Models, Identity Verification, Online Dating, Social Media, Software Product Lines, Trustworthiness Assessment
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Synopsis

            
The publication addresses how software engineers can better support users in assessing trustworthiness when interacting with strangers online through computer-mediated introductions such as dating apps or sharing-economy services. The authors propose a model‑based approach that extends feature models to capture trust-related properties and nudges, with the goal of helping design interactive applications that raise awareness, trigger, and enable online trustworthiness assessments. Their approach adapts feature models by labeling software features as awareness, trigger, or empowerment types, and by attaching trustworthiness facets as attributes. Facets are differentiated for three parties—the user, the platform, and the service provider—and are color‑coded to reflect their focus (green for user-to-user trust, orange for platform trust, purple for brand trust). The authors outline a two‑phase facet attribution process (allocation and propagation) to ensure that parent features reflect the combined impact of their subfeatures on trustworthiness. They also present a three‑phase method for applying the models: model creation, validation, and software product line configuration, supported by a proposed catalogue structure that helps keep feature information consistent and reusable. A concrete example uses catfishing protection in online dating and centers on an identity‑verification empowerment feature. The example demonstrates how a verification algorithm, user profile indicators (such as a green check mark), and status notifications can be modeled and annotated with trustworthiness facets, illustrating the potential design options and validation pathways. The authors acknowledge limitations, including the risk of facet overloading, halo effects, and the need for further empirical validation and tool support to manage large variability in practice. Overall, the work offers a structured, reusable approach to embed trust considerations into CMI software design.

          

        
                  

            
Identified Gaps

            
The paper identifies gaps in validation of trustworthiness facets, particularly where no scientific scales exist. It notes that validation currently addresses only facets identified by engineers, overlooking relevant unidentified facets. It also identifies limited understanding of halo effects, the distinction between platform and service-provider trustworthiness perceptions, practitioner acceptance, and which feature/facet configurations best support assessments without excessive complexity.

          

        
                  

            
Methods

            
The paper proposes an extended feature-model method for computer-mediated-introduction applications. Engineers first define a problem and model awareness, trigger, and empowerment features. They then allocate trustworthiness facets to features and propagate facets from child to parent features. Proposed validation uses prototypes, usability testing, facet ratings, and feature-type measures; the models can then support software-product-line configuration. An identity-verification model for catfish protection in online dating illustrates the approach.

          

        
                  

            
Limitations

            
Feature-model creation depends on the subjective judgments of the software engineer, which can produce mistakes or omit relevant trustworthiness facets. Halo effects may distort both facet allocation and users’ perceived traits. Distinguishing platform from service-provider facets is difficult. The large number of features and facets can create cluttered models and make product-line configuration more complex. The proposed method and example are not empirically validated in this paper.

          

        
                  

            
Future Work

            
Develop validation techniques for whether features address trustworthiness facets and affect assessments. Create scales for facets without scientific measures. Examine halo effects, including unidentified facets and distinctions between platform and service-provider facets. Test practitioner acceptance and improve the method empirically. Assess feature-set configurations, variability/commonality tradeoffs, and use usability testing to determine effective configurations.

          

              

    
    

        
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