Interactive Reputation Systems

Sänger, Johannes; Pernul, Günther

doi:10.1007/s12599-017-0493-1

Cited by 8 publications

(5 citation statements)

References 38 publications

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“…The figure basically presents a co-owned data sharing process, which includes a group of people taking a group decision. In this process, the data owner uploads a content of data, either from a storage or can produce a content of data with any IoT devices [34]. The owner decides who is going to access the content (i.e.…”

Section: Preliminariesmentioning

confidence: 99%

Towards Consensus-Based Group Decision Making for Co-Owned Data Sharing in Online Social Networks

2020

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The use of online social networks has become a crucial activity for individuals in recent years. Users have started to share more data in online social networking platforms. The shared content sometimes includes more than one user's information. This type of data sharing has caused privacy issues as users are only informed after the sharing process is completed. Although, many of the current studies have focused on applying group decision making in data sharing processes, this technique remains a challenge. In this study, we provide a framework in which a consensus-based group decision making process is used in order to take the best decision in co-owned data sharing processes in online social networking. INDEX TERMS Consensus-reaching, co-owned data sharing, fuzzy decision making systems, group decision making, online social networks, users trust values. MO ADDA received the Ph.D. degree in distributed systems and parallel processing from the University of Surrey. He was a Senior Lecturer with the University of Richmond, where he taught programming, computer architecture, and networking, for ten years. From 1999 to 2002, he was a Senior Software Engineer developing software and managing projects on simulation and modeling. He has been researching parallel and distributed systems, since 1987. He is currently a Principal Lecturer in computer networks with the School of Computing, University of Portsmouth. His research interests include software-defined networks, wireless sensor networks, mobile networks, and business process modeling, simulation of mobile agent technology.

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Section: Preliminariesmentioning

confidence: 99%

Towards Consensus-Based Group Decision Making for Co-Owned Data Sharing in Online Social Networks

2020

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“…Moreover, operators use different colors (e.g., yellow, red, blue) to display the rating or vary the colors within the scale. The specification of the evaluation can be highlighted using different colors (Kornberger et al 2017;Sänger and Pernul 2018).…”

Section: Table 1 Morphological Box Of Feedback Mechanismsmentioning

confidence: 99%

“…Possible reasons for this dysfunctional effect include incorrectly designed feedback mechanisms, such as reciprocal mechanisms in which users take revenge for negative feedback (Bolton et al 2013). In addition to the behavioral economic aspects, there is further literature on various forms of manipulation, their detection, and their design to prevent manipulation (e.g., Hoffman et al 2009;Jøsang et al 2007;Mayzlin et al 2014;Sänger and Pernul 2018). Platform operators should seek to avoid manipulations, such as ballot stuffing, badmouthing and Sybil attacks (Hoffman et al 2009).…”

Section: Table 1 Morphological Box Of Feedback Mechanismsmentioning

confidence: 99%

“…In the next step, we checked the remaining 336 websites for the existence of a digital platform using the same characteristics than Steur and Bayrle (2020). In particular, a platform required the presence of two or more market sides, an intermediary providing a digital infrastructure, interactions between the different market sides, and network effects (Armstrong 2006;Brousseau and Penard 2007;Rochet and Tirole 2003;Tiwana 2014). For the selection, we used a similar classification of websites developed by Dorfer (2016).…”

Section: Descriptive Analysismentioning

confidence: 99%

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Properties of feedback mechanisms on digital platforms: an exploratory study

Steur

Seiter

2020

J Bus Econ

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Many digital platforms implement feedback mechanisms as a means to control the behavior of their users. However, there is a lack of theoretical explanation regarding the interrelation between design characteristics of feedback mechanisms and their effects. In this study, we interpret feedback mechanisms as a specific type of management control to propose properties as a new theoretical perspective on this problem. Our exploratory study has two objectives. First, we analyze how digital platforms design their feedback mechanisms. Second, we examine to what extent feedback mechanisms comply with standards given in the management control literature for our newly introduced properties. Analyzing the 102 most widely used platforms in Germany, we find dominant patterns in nearly all design characteristics (e.g., query method, submission category and scale level). Furthermore, we find mixed compliance of feedback mechanisms with our introduced properties (e.g., low precision but high sensitivity and verifiability). For a deeper understanding of these results, especially the reasons for the design choices, we conduct 14 semi-structured expert interviews. We find simplicity and inspiration from other platforms to be dominant drivers for design choices.

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“…However, these studies tend to view online market institutions as merely technical aspects without fully elaborating on the social interaction processes mediated by the internet. Sänger and Pernul (2018) criticized reputation systems that can be manipulated and introduced the concept of interactive reputation systems involving users in assessing reputation, thus enhancing the ability to detect inconsistent behavior.…”

Section: Introductionmentioning

confidence: 99%

Reputation System as a Digital Socio-Economic Institution: Willingness to Sell in Online Markets

Elfena

2024

Temali.

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This study examines the features and big data consisting of digital trace records from economic actions within Bukalapak's reputation system and their impact on the willingness to sell (WTS) electronic products. Digital mixed content analysis was used to analyze the rapidly evolving digital-social-based economic institution infrastructure. Data were collected, analyzed, and visualized using Python and analyzed using the concepts of new economic institutions and WTS. The findings indicate that the reputation system is a formal element comprising algorithms, rules, scripts, and patterns. This system facilitates social processes through feedback mechanisms in product descriptions, comments, reviews, ratings, and badges, which generate informal elements such as norms, trust, and symbolic values. These two elements are interconnected into an institutional framework whose function is to ensure that the market, characterized by high levels of anonymous transactions, uncertainty, and asymmetric information, can remain stable and meet the expectations of the actors involved.

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Interactive Reputation Systems

Cited by 8 publications

References 38 publications

Towards Consensus-Based Group Decision Making for Co-Owned Data Sharing in Online Social Networks

Towards Consensus-Based Group Decision Making for Co-Owned Data Sharing in Online Social Networks

Properties of feedback mechanisms on digital platforms: an exploratory study

Reputation System as a Digital Socio-Economic Institution: Willingness to Sell in Online Markets

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