844 resultados para Distributed Social Networks
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Word of mouth (WOM) communication is a major part of online consumer interactions, particularly within the environment of online communities. Nevertheless, existing (offline) theory may be inappropriate to describe online WOM and its influence on evaluation and purchase.The authors report the results of a two-stage study aimed at investigating online WOM: a set of in-depth qualitative interviews followed by a social network analysis of a single online community. Combined, the results provide strong evidence that individuals behave as if Web sites themselves are primary "actors" in online social networks and that online communities can act as a social proxy for individual identification. The authors offer a conceptualization of online social networks which takes the Web site into account as an actor, an initial exploration of the concept of a consumer-Web site relationship, and a conceptual model of the online interaction and information evaluation process. © 2007 Wiley Periodicals, Inc. and Direct Marketing Educational Foundation, Inc.
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Sales leadership research has typically taken a leader-focused approach, investigating key questions from a top-down perspective. Yet considerable research outside sales has advocated a view of leadership that takes into account the fact that employees look beyond a single designated individual for leadership. In particular, the social networks of leaders have been a popular topic of investigation in the management literature, although coverage in the sales literature remains rare. The present paper conceptualizes the sales leadership role as one in which the leader must manage a network of simultaneous relationships; several types of sales manager relationships, such as the sales-manager-to-top-manager and the sales-manager-to-sales manager relationships, have received limited attention in the sales literature to date. Taking an approach based on social network theory, we develop a conceptualization of the sales manager as a "network engineer," who must manage multiple relationships, and the flows between them. Drawing from this model, we propose a detailed agenda for future sales research. © 2012 PSE National Educational Foundation. All rights reserved.
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The low-energy consumption of IEEE 802.15.4 networks makes it a strong candidate for machine-to-machine (M2M) communications. As multiple M2M applications with 802.15.4 networks may be deployed closely and independently in residential or enterprise areas, supporting reliable and timely M2M communications can be a big challenge especially when potential hidden terminals appear. In this paper, we investigate two scenarios of 802.15.4 network-based M2M communication. An analytic model is proposed to understand the performance of uncoordinated coexisting 802.15.4 networks. Sleep mode operations of the networks are taken into account. Simulations verified the analytic model. It is observed that reducing sleep time and overlap ratio can increase the performance of M2M communications. When the networks are uncoordinated, reducing the overlap ratio can effectively improve the network performance. © 2012 Chao Ma et al.
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Intelligent transport system (ITS) has large potentials on road safety applications as well as nonsafety applications. One of the big challenges for ITS is on the reliable and cost-effective vehicle communications due to the large quantity of vehicles, high mobility, and bursty traffic from the safety and non-safety applications. In this paper, we investigate the use of dedicated short-range communications (DSRC) for coexisting safety and non-safety applications over infrastructured vehicle networks. The main objective of this work is to improve the scalability of communications for vehicles networks, ensure QoS for safety applications, and leave as much as possible bandwidth for non-safety applications. A two-level adaptive control scheme is proposed to find appropriate message rate and control channel interval for safety applications. Simulation results demonstrated that this adaptive method outperforms the fixed control method under varying number of vehicles. © 2012 Wenyang Guan et al.
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In this paper, we explore the idea of social role theory (SRT) and propose a novel regularized topic model which incorporates SRT into the generative process of social media content. We assume that a user can play multiple social roles, and each social role serves to fulfil different duties and is associated with a role-driven distribution over latent topics. In particular, we focus on social roles corresponding to the most common social activities on social networks. Our model is instantiated on microblogs, i.e., Twitter and community question-answering (cQA), i.e., Yahoo! Answers, where social roles on Twitter include "originators" and "propagators", and roles on cQA are "askers" and "answerers". Both explicit and implicit interactions between users are taken into account and modeled as regularization factors. To evaluate the performance of our proposed method, we have conducted extensive experiments on two Twitter datasets and two cQA datasets. Furthermore, we also consider multi-role modeling for scientific papers where an author's research expertise area is considered as a social role. A novel application of detecting users' research interests through topical keyword labeling based on the results of our multi-role model has been presented. The evaluation results have shown the feasibility and effectiveness of our model.
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Autism is a developmental disorder that is currently defined in terms of a triad of impairments in social interaction, communication, and behavioural flexibility. Psychological models have focussed on deficits in high level social and cognitive processes, such as ‘weak central coherence’ and deficits in ‘theory of mind’. Converging evidence from different fields of neuroscience research indicates that the underlying neural dysfunction is associated with atypical patterns of cortical connectivity (Rippon et al., 2007). This arises very early in development and results in sensory, perceptual and cognitive deficits at a much earlier and more fundamental level than previously suggested, but with cascading effects on higher level psychological and social processes. Earlier research in this sphere has focussed mainly on patterns of underconnectivity in distributed cortical networks underpinning process such as language and executive function. (Just et al., 2007). Such research mainly utilises imaging techniques with high spatial resolution. This paper focuses on evidence associated with local over-connectivity, evident in more low level and transitory processes and hence more easily measurable with techniques with high temporal resolution, such as MEG and EEG. Results are described which provide evidence of such local over-connectivity, characterised by atypical results in the gamma frequency range (Brown et al., 2005) together with discussions about the future directions of such research and its implications for remediation.
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The energy balancing capability of cooperative communication is utilized to solve the energy hole problem in wireless sensor networks. We first propose a cooperative transmission strategy, where intermediate nodes participate in two cooperative multi-input single-output (MISO) transmissions with the node at the previous hop and a selected node at the next hop, respectively. Then, we study the optimization problems for power allocation of the cooperative transmission strategy by examining two different approaches: network lifetime maximization (NLM) and energy consumption minimization (ECM). For NLM, the numerical optimal solution is derived and a searching algorithm for suboptimal solution is provided when the optimal solution does not exist. For ECM, a closed-form solution is obtained. Numerical and simulation results show that both the approaches have much longer network lifetime than SISO transmission strategies and other cooperative communication schemes. Moreover, NLM which features energy balancing outperforms ECM which focuses on energy efficiency, in the network lifetime sense.
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Editorial
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Existing approaches of social influence analysis usually focus on how to develop effective algorithms to quantize users' influence scores. They rarely consider a person's expertise levels which are arguably important to influence measures. In this paper, we propose a computational approach to measuring the correlation between expertise and social media influence, and we take a new perspective to understand social media influence by incorporating expertise into influence analysis. We carefully constructed a large dataset of 13,684 Chinese celebrities from Sina Weibo (literally 'Sina microblogging'). We found that there is a strong correlation between expertise levels and social media influence scores. In addition, different expertise levels showed influence variation patterns: high-expertise celebrities have stronger influence on the 'audience' in their expertise domains.
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Report published in the Proceedings of the National Conference on "Education and Research in the Information Society", Plovdiv, May, 2014
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In many e-commerce Web sites, product recommendation is essential to improve user experience and boost sales. Most existing product recommender systems rely on historical transaction records or Web-site-browsing history of consumers in order to accurately predict online users’ preferences for product recommendation. As such, they are constrained by limited information available on specific e-commerce Web sites. With the prolific use of social media platforms, it now becomes possible to extract product demographics from online product reviews and social networks built from microblogs. Moreover, users’ public profiles available on social media often reveal their demographic attributes such as age, gender, and education. In this paper, we propose to leverage the demographic information of both products and users extracted from social media for product recommendation. In specific, we frame recommendation as a learning to rank problem which takes as input the features derived from both product and user demographics. An ensemble method based on the gradient-boosting regression trees is extended to make it suitable for our recommendation task. We have conducted extensive experiments to obtain both quantitative and qualitative evaluation results. Moreover, we have also conducted a user study to gauge the performance of our proposed recommender system in a real-world deployment. All the results show that our system is more effective in generating recommendation results better matching users’ preferences than the competitive baselines.
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Van egy szó, ami egyre fontosabb lesz a társadalom és a vállalatok számára is, ez a szó a közösség. A közösséghez tevékenységek tartoznak, és ezen a ponton kapcsolódik be a vállalat. A vállalkozások az elmúlt években a közösségi igényeket a CRM-(Customer Relationship Management) megoldásokkal szolgálták ki. Informatikailag a közösségi hálózatok, már nemcsak vállalkozási folyamatot, hanem ehhez kapcsoltan az emberek társadalmi igényét is megpróbálják lefedni az elektronika lehetőségeivel. Egyre inkább a közösségi vállalkozások korát éljük, melyben a folyamathoz tartozó közösségek megosztják, egymás rendelkezésére bocsátják az információkat. A korábbi klasszikus CRM-rendszerek csak begyűjtötték az információkat, ezzel ellenben a közösségi CRM-rendszerek kétirányú kommunikációt folytatnak, párbeszédet kezdeményeznek az ügyfelekkel, buzdítják őket, hogy mondják el a véleményüket. Vajon ez az új stratégia,egy teljesen új világot hoz el a vállalatok számára, vagy csak a CRM fejlődésének egy újabb fokát jelenti? A szerzők erre a kérdésre keresik a választ gyakorlati esetek és szakirodalmi publikációk feldolgozásával. ______ There is a word that begins to be more and more important for the society and the companies, and this word is community. We can talk about social networks, people seek the social demand they already had as a part of their lives for a long time, and this means that it appears in the electronic society as an essential need too. The community is not enough, activities are also needed and this is the point where the companies link in, who promote their goods and facilities to the outside world and with this they use the next stage of customer relationship management, the fulfilment of social needs. We live in the age of social shopping, communities are everywhere and everyone shares information, and up to the present classic CR M systems ran from static databases. On the contrary social CR M systems perform a two-way communication, start a conversation with customers and encourage them to tell their opinions, which always changes on social media, so they build a dynamic database and communicate with customers through response-reactions. Does this new strategy bring a whole new world to companies or is it only another step in the development and another channel of CRM?