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While the recent discussion on Art. 25 GDPR often considers the approach of data protection by design as an innovative idea, the notion of making data protection law more effective through requiring the data controller to implement the legal norms into the processing design is almost as old as the data protection debate. However, there is another, more recent shift in establishing the data protection by design approach through law, which is not yet understood to its fullest extent in the debate. Art. 25 GDPR requires the controller to not only implement the legal norms into the processing design but to do so in an effective manner. By explicitly declaring the effectiveness of the protection measures to be the legally required result, the legislator inevitably raises the question of which methods can be used to test and assure such efficacy. In our opinion, extending the legal compatibility assessment to the real effects of the required measures opens this approach to interdisciplinary methodologies. In this paper, we first summarise the current state of research on the methodology established in Art. 25 sect. 1 GDPR, and pinpoint some of the challenges of incorporating interdisciplinary research methodologies. On this premise, we present an empirical research methodology and first findings which offer one approach to answering the question on how to specify processing purposes effectively. Lastly, we discuss the implications of these findings for the legal interpretation of Art. 25 GDPR and related provisions, especially with respect to a more effective implementation of transparency and consent, and provide an outlook on possible next research steps.
Background
Consumers rely heavily on online user reviews when shopping online and cybercriminals produce fake reviews to manipulate consumer opinion. Much prior research focuses on the automated detection of these fake reviews, which are far from perfect. Therefore, consumers must be able to detect fake reviews on their own. In this study we survey the research examining how consumers detect fake reviews online.
Methods
We conducted a systematic literature review over the research on fake review detection from the consumer-perspective. We included academic literature giving new empirical data. We provide a narrative synthesis comparing the theories, methods and outcomes used across studies to identify how consumers detect fake reviews online.
Results
We found only 15 articles that met our inclusion criteria. We classify the most often used cues identified into five categories which were (1) review characteristics (2) textual characteristics (3) reviewer characteristics (4) seller characteristics and (5) characteristics of the platform where the review is displayed.
Discussion
We find that theory is applied inconsistently across studies and that cues to deception are often identified in isolation without any unifying theoretical framework. Consequently, we discuss how such a theoretical framework could be developed.
Eco-InfoVis at Work
(2020)