937 resultados para Social network site


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The skyrocketing trend for social media on the Internet greatly alters analytical Customer Relationship Management (CRM). Against this backdrop, the purpose of this paper is to advance the conceptual design of Business Intelligence (BI) systems with data identified from social networks. We develop an integrated social network data model, based on an in-depth analysis of Facebook. The data model can inform the design of data warehouses in order to offer new opportunities for CRM analyses, leading to a more consistent and richer picture of customers? characteristics, needs, wants, and demands. Four major contributions are offered. First, Social CRM and Social BI are introduced as emerging fields of research. Second, we develop a conceptual data model to identify and systematize the data available on online social networks. Third, based on the identified data, we design a multidimensional data model as an early contribution to the conceptual design of Social BI systems and demonstrate its application by developing management reports in a retail scenario. Fourth, intellectual challenges for advancing Social CRM and Social BI are discussed.

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Enterprise social networks are organizationally bounded online platforms for users to interact with another and maintain interpersonal relationships. The allure of these technologies is often seen in intra-organizational communication, collaboration and innovation. How these technologies actually support organizational innovation efforts remains unclear. A specific challenge is whether digital content on these platforms converts to actual innovation development efforts. In this study we set out to examine innovation-centric content flows on enterprise social networking platforms, and advance a conceptual model that seeks to explain which innovation conveyed in the digital content will traverse from the digital platform into regular processes. We describe important constructs of our model and offer strategies for the operationalization of the constructs. We conclude with an outlook to our ongoing empirical study that will explore and validate the key propositions of our model, and we sketch some potential implications for industry and academia.

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Organizations employ Enterprise Social Networks (ESNs) (e.g., Yammer) expecting better intra-organizational communication, effective knowledge sharing and, in general, greater collaboration. Despite their similarities with Public Social Networks (PSNs) (e.g., Twitter), ESNs are struggling to gain credence with employees. This paper is part of a larger research project that investigates mechanisms to enhance employees’ engagement in the ESNs. Through the lens of Control Theory, this paper reports preliminary findings of a pilot case study aimed to propose formal and informal mechanisms that impact employees’ intrinsic and extrinsic motivations to encourage their use of ESNs. The study results highlight (i) the need to better understand employees’ extrinsic and intrinsic motivations to use Social Networks, and (ii) that unlike a PSN which acts as a hedonic system, an ESN acts as a utilitarian system, highlighting the importance of supporting intrinsic motivations in its implementation.

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Detecting anomalies in the online social network is a significant task as it assists in revealing the useful and interesting information about the user behavior on the network. This paper proposes a rule-based hybrid method using graph theory, Fuzzy clustering and Fuzzy rules for modeling user relationships inherent in online-social-network and for identifying anomalies. Fuzzy C-Means clustering is used to cluster the data and Fuzzy inference engine is used to generate rules based on the cluster behavior. The proposed method is able to achieve improved accuracy for identifying anomalies in comparison to existing methods.

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Social Networks (SN) users have various privacy requirements to protect their information; to address this issue, a six-stage thematic analysis of scholarly articles related to SN user privacy concerns were synthesized. Then this research combines mixed methods research employing the strengths of quantitative and qualitative research to investigate general SN users, and thus construct a new set of ?ve primary and Twenty-?ve secondary SN user privacy requirements. Such an approach has been rarely used to examine the privacy requirements. Factor analysis results show superior agreement with theoretical predictions and signi?cant improvement over previous alternative models of SN user privacy requirements. This research presented here has the potential to provide for the development of more sophisticated privacy controls which will increase the ability of SN users to: specify their rights in SNs and to determine the protection of their own SN data.

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This study extends previous research into social networking sites (SNSs) as environments that often reduce spatial, temporal, and social boundaries, which can result in collapsed contexts for social situations. Context collapse was investigated through interviews and Facebook walkthroughs with 27 LGBTQ young people in the United Kingdom. Since diverse sexualities are often stigmatized, participants’ sexual identity disclosure decisions were shaped by both the social conditions of their online networks and the technological architecture of SNSs. Context collapse was experienced as an event through which individuals intentionally redefined their sexual identity across audiences or managed unintentional disclosure. To prevent unintentional context collapse, participants frequently reinstated contexts through tailored performances and audience separation. These findings provide insight into stigmatized identity performances in networked publics while situating context collapse within a broader understanding of impression management, which paves the way for future research exploring the identity implications of everyday SNS use.

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This paper presents two key findings from a longitudinal study examining the dynamics of social networks during organisational change. One, the degree to which users seek new sources of information while adapting to the change. Two, the degree to which social networks display structural resilience when undergoing significant structural and technological change. Users reported an increase in advice ties post-implementation, however a proportionally higher increase in ties within their work group compared to the wider network was identified. The results also supported the supposition that while IT driven change may initially disrupt social networks some networks possess a high degree of resilience, with key players reasserting their original positions of influence following the initial phase of change related disruption.

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Understanding the dynamics of disease spread is essential in contexts such as estimating load on medical services, as well as risk assessment and interven- tion policies against large-scale epidemic outbreaks. However, most of the information is available after the outbreak itself, and preemptive assessment is far from trivial. Here, we report on an agent-based model developed to investigate such epidemic events in a stylised urban environment. For most diseases, infection of a new individual may occur from casual contact in crowds as well as from repeated interactions with social partners such as work colleagues or family members. Our model therefore accounts for these two phenomena. Given the scale of the system, efficient parallel computing is required. In this presentation, we focus on aspects related to paralllelisation for large networks generation and massively multi-agent simulations.

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Successful project management depends upon forming and maintaining relationships between and among project team members and stakeholder groups. The nature of these relationships and the patterns that they form affect communication, collaboration and resource flows. Networks affect us directly, and we use them to influence people and processes. Social Network Analysis (SNA) can be an extremely valuable research tool to better understand how critical social networks develop and influence work processes, particularly as projects become larger and more complex. This chapter introduces foundational network concepts, helps you determine if SNA could help you answer your research questions, and explains how to design and implement a social network study. At the end of this chapter, the reader can: understand foundational concepts about social networks; decide if SNA is an appropriate research methodology to address particular questions or problems; design and implement a basic social network study.

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A major question in current network science is how to understand the relationship between structure and functioning of real networks. Here we present a comparative network analysis of 48 wasp and 36 human social networks. We have compared the centralisation and small world character of these interaction networks and have studied how these properties change over time. We compared the interaction networks of (1) two congeneric wasp species (Ropalidia marginata and Ropalidia cyathiformis), (2) the queen-right (with the queen) and queen-less (without the queen) networks of wasps, (3) the four network types obtained by combining (1) and (2) above, and (4) wasp networks with the social networks of children in 36 classrooms. We have found perfect (100%) centralisation in a queen-less wasp colony and nearly perfect centralisation in several other queen-less wasp colonies. Note that the perfectly centralised interaction network is quite unique in the literature of real-world networks. Differences between the interaction networks of the two wasp species are smaller than differences between the networks describing their different colony conditions. Also, the differences between different colony conditions are larger than the differences between wasp and children networks. For example, the structure of queen-right R. marginata colonies is more similar to children social networks than to that of their queen-less colonies. We conclude that network architecture depends more on the functioning of the particular community than on taxonomic differences (either between two wasp species or between wasps and humans).

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Over the past two decades, the poultry sector in China went through a phase of tremendous growth as well as rapid intensification and concentration. Highly pathogenic avian influenza virus (HPAIV) subtype H5N1 was first detected in 1996 in Guangdong province, South China and started spreading throughout Asia in early 2004. Since then, control of the disease in China has relied heavily on wide-scale preventive vaccination combined with movement control, quarantine and stamping out. This strategy has been successful in drastically reducing the number of outbreaks during the past 5 years. However, HPAIV H5N1 is still circulating and is regularly isolated in traditional live bird markets (LBMs) where viral infection can persist, which represent a public health hazard for people visiting them. The use of social network analysis in combination with epidemiological surveillance in South China has identified areas where the success of current strategies for HPAI control in the poultry production sector may benefit from better knowledge of poultry trading patterns and the LBM network configuration as well as their capacity for maintaining HPAIV H5N1 infection. We produced a set of LBM network maps and estimated the associated risk of HPAIV H5N1 within LBMs and along poultry market chains, providing new insights into how live poultry trade and infection are intertwined. More specifically, our study provides evidence that several biosecurity factors such as daily cage cleaning, daily cage disinfection or manure processing contribute to a reduction in HPAIV H5N1 presence in LBMs. Of significant importance is that the results of our study also show the association between social network indicators and the presence of HPAIV H5N1 in specific network configurations such as the one represented by the counties of origin of the birds traded in LBMs. This new information could be used to develop more targeted and effective control interventions.

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Amateurs are found in arts, sports, or entertainment, where they are linked with professional counterparts and inspired by celebrities. Despite the growing number of CSCW studies in amateur and professional domains, little is known about how technologies facilitate collaboration between these groups. Drawing from a 1.5-year field study in the domain of bodybuilding, this paper describes the collaboration between and within amateurs, professionals, and celebrities on social network sites. Social network sites help individuals to improve their performance in competitions, extend their support network, and gain recognition for their achievements. The findings show that amateurs benefit the most from online collaboration, whereas collaboration shifts from social network sites to offline settings as individuals develop further in their professional careers. This shift from online to offline settings constitutes a novel finding, which extends previous work on social network sites that has looked at groups of amateurs and professionals in isolation. As a contribution to practice, we highlight design factors that address this shift to offline settings and foster collaboration between and within groups.