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TEMİZKAN, Orçun

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    Knowledge transfer to aid social coding: The case of Stack Overflow
    (Elsevier, 2024-04) Temizkan, Orçun; Kumar, R. L.; Management Information Systems; TEMİZKAN, Orçun
    Focused online question and answer (Q&A) communities aid social coding. Despite the growing importance of social coding, knowledge transfer in this context remains under-researched. Our primary objective is to understand the knowledge transfer process in this context. We conceptualize knowledge transfer as a process that is impacted by the prior knowledge transfer interactions (network) among participants and is augmented by gamification. We argue that social capital resulting from prior knowledge transfer network interactions impact answer quality. Moreover, we also argue that the relationship between social capital and answer quality is moderated by the complexity of the knowledge transferred. Hence, our models draw from multiple related research streams: online communities, knowledge transfer, social capital, and gamification. These models are empirically tested using data from Stack Overflow (SO), a popular online Q&A community that aids social coding. Our results help to understand knowledge transfer in Q&A communities that aid social coding. Moreover, our results have implications for research on other types of Q&A communities and can inform development of platforms to support online communities.
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    Software diversity for improved network security: optimal distribution of software-based shared vulnerabilities
    (Informs, 2017-12) Temizkan, Orçun; Park, S.; Saydam, C.; Management Information Systems; TEMİZKAN, Orçun
    Firms, and other agencies, tend to adopt widely used software to gain economic benefits of scale, which can lead to a software monoculture. This can, in turn, involve the risk of correlated computer systems failure as all systems on the network are exposed to the same software-based vulnerabilities. Software diversity has been introduced as a strategy for disrupting such a monoculture and ultimately decreasing the risk of correlated failure. Nevertheless, common vulnerabilities can be shared by different software products. We thus expand software diversity research here and consider shared vulnerabilities between different software alternatives. We develop a combinatorial optimization model of software diversity on a network in an effort to identify the optimal software distribution that best improves network security. We also develop a simulation model of virus propagation based on the susceptible-infected-susceptible model. This model allows calculation of the epidemic threshold, a measure of network resilience to virus propagation. We then test the effectiveness of the proposed software diversity strategies against the spreading of viruses through a series of experiments.