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1.
Steven Casper 《Research Policy》2007,36(4):438-455
Regional technology clusters are an important source of economic development, yet in biotechnology few successful clusters exist. Previous research links successful clusters to heightened innovation capacity achieved through the existence of social ties linking individuals across companies. Less understood are the mechanisms by which such networks emerge. The article uses social network analysis to examine the emergence of social networks linking senior managers employed in biotechnology firms in San Diego, California. Labor mobility within the region has forged a large network linking managers and firms, while ties linking managers of an early company, Hybritech, formed a network backbone anchoring growth in the region. 相似文献
2.
《Information processing & management》2020,57(6):102317
The problem of social spam detection has been traditionally modeled as a supervised classification problem. Despite the initial success of this detection approach, later analysis of proposed systems and detection features has shown that, like email spam, the dynamic and adversarial nature of social spam makes the performance achieved by supervised systems hard to maintain. In this paper, we investigate the possibility of using the output of previously proposed supervised classification systems as a tool for spammers discovery. The hypothesis is that these systems are still highly capable of detecting spammers reliably even when their recall is far from perfect. We then propose to use the output of these classifiers as prior beliefs in a probabilistic graphical model framework. This framework allows beliefs to be propagated to similar social accounts. Basing similarity on a who-connects-to-whom network has been empirically critiqued in recent literature and we propose here an alternative definition based on a bipartite users-content interaction graph. For evaluation, we build a Markov Random Field on a graph of similar users and compute prior beliefs using a selection of state-of-the-art classifiers. We apply Loopy Belief Propagation to obtain posterior predictions on users. The proposed system is evaluated on a recent Twitter dataset that we collected and manually labeled. Classification results show a significant increase in recall and a maintained precision. This validates that formulating the detection problem with an undirected graphical model framework permits to restore the deteriorated performances of previously proposed statistical classifiers and to effectively mitigate the effect of spam evolution. 相似文献
3.
Toward alternative metrics of journal impact: A comparison of download and citation data 总被引：2，自引：0，他引：2
We generated networks of journal relationships from citation and download data, and determined journal impact rankings from these networks using a set of social network centrality metrics. The resulting journal impact rankings were compared to the ISI IF. Results indicate that, although social network metrics and ISI IF rankings deviate moderately for citation-based journal networks, they differ considerably for journal networks derived from download data. We believe the results represent a unique aspect of general journal impact that is not captured by the ISI IF. These results furthermore raise questions regarding the validity of the ISI IF as the sole assessment of journal impact, and suggest the possibility of devising impact metrics based on usage information in general. 相似文献
4.
日益兴起的社会网络负功能研究,修正了以往过度重视积极效应的认识误区,逐渐成为社会网络研究的核心话题。本文基于企业层面,对相关领域的文献进行总结梳理后发现,企业社会网络的负功能可作用于微观、中观和宏观三个层面,分别表现为限制组织成员的创造力、导致企业面临"负债"困境、促使市场分割与地方保护主义的形成。在影响因素的研究中,现有的分析框架可归纳为网络结构主义和组织环境两种理论视角,网络排他性、过度嵌入、市场需求的不确定性、技术动荡、企业生命周期与战略目标均对社会网络负功能的发生产生重要作用。在此基础上,本文从研究视角、内容、方法和理论建构四个方面提出未来研究的发展方向。 相似文献
5.
本文对基于复杂网络社会动力学进行了全面的研究,讨论了社会网络包含的具体内容,着重介绍了度与度分布,加权网络及社团结构及聚类算法与社会网络动力学的关联,并关注社会网络鲁棒性与社会网络自组织临界性研究等动力学具体表现,为目前的社会网络动力学分析提供一种比较实用的研究方法。 相似文献
6.
《Information processing & management》2020,57(4):102237
This paper analyses how the knowledge shared between employees and suppliers within a private enterprise social network affects process improvement. Data was collected from internal documents, and the internal and external enterprise social networks used by an international insurance company; the average cycle time for handling 8494 claims and 3240 messages posted on the internal and external social networks was analysed. Social network analysis techniques were combined with principal component analysis and structural equation modeling, and the results demonstrate that the knowledge shared within the internal and external social network can explain 35.10% of process improvement variability, while the knowledge shared within the internal social network explains 89.90% of external social network variability. The analysis also demonstrates that: (i) the knowledge shared among employees positively affects process improvement; (ii) the knowledge shared among suppliers negatively affects process improvement; and (iii) the knowledge shared among employees positively affects the knowledge shared among supply chain members. These findings have theoretical and practical implications. They extend the literature in the knowledge management and information management field by offering empirical evidence of how the knowledge shared through an enterprise social network affects business process improvement, using the objective data provided by Yammer. They also provide a strategic tool for managers that will allow them to better understand how they can use the enterprise social network for business processes improvement. 相似文献
7.
《Information processing & management》2016,52(6):1053-1073
Spam in recent years has pervaded all forms of digital communication.The increase in user base for social platforms like Facebook, Twitter, YouTube, etc., has opened new avenues for spammers. The liberty to contribute content freely has encouraged the spammers to exploit the social platforms for their benefits. E-mail and web search engine being the early victims of spam have attracted serious attention from the information scientists for quite some time. A substantial amount of research has been directed to combat spam on these two platforms. Social networks being quite different in nature from the earlier two, have different kinds of spam and spam-fighting techniques from these domains seldom work. Moreover, due to the continuous and rapid evolution of social media, spam themselves evolve very fast posing a great challenge to the community. Despite being relatively new, there has been a number of attempts in the area of social spam in the recent past and a lot many are certain to come in near future. This paper surveys the recent developments in the area of social spam detection and mitigation, its theoretical models and applications along with their qualitative comparison. We present the state-of-the-art and attempt to provide challenges to be addressed, as the nature and content of spam are bound to get more complicated. 相似文献
8.
以广东省卫生厅某直属医院重点科室作为研究对象,通过问卷调查,分析该科室团队的社会网络结构、社会网络关系强度及知识创新强度.发现该团队知识创新的社会网络结构较松散,连接线多处于个人网络内部;网络中存在一定数量的程度中心性和中介中心性高的节点;年龄和学历均为社会网络关系强度和知识创新程度的影响因素;社会网络结构与社会网络关系、知识创新呈显著正相关,社会网络关系与知识创新呈显著正相关.旨在为探讨公立医院知识创新社会网络结构特征提供范例,进而为公立医院增强知识创新和科技创新能力提供借鉴. 相似文献
9.
组织合作网络结构对企业绩效的影响有两类相反的作用机制：网络闭合和网络开放。论文认为,哪种机制起作用取决于企业所面临的创新任务以及知识来源在网络中的位置。基于汤森路透、USPTO和Compustat三个数据库,论文构建1990-2001年生物技术和医药产业追踪数据,采用社会网络分析方法、固定效应和随机效应模型对此问题进行实证研究。结果发现,战略联盟网络密度增加和结构洞指标增加会负向影响企业技术创新数量,正向影响企业技术创新质量;网络结构调节着直接联盟关系和间接联盟关系对企业技术创新的影响。 相似文献
10.
Social networks are becoming a key communication tool for organizations, but also for top managers like CEOs. Among the different available platforms, Twitter is one of the greatest and it is considered one of the most suitable to share information and engage in dialogue with stakeholders. In this way, this paper analyzes the presence of CEOs on the most active social network sites, and assess the activity and interaction of these top managers on Twitter. CEOs from Global and Latin American companies were selected, to compare their performance. The results of the study show that the presence of CEOs in social networks is very low, and the majority of those that are present on them are not adequately using their Twitter accounts. Although the general presence and performance on are low, LatAm CEOs have a better presence on social networks and they are more active on Twitter, but Global CEOs have better interaction results on their accounts. So, this area of strategic communication should be improved by communication practitioners, since the CEO communication is nowadays a key communication issue for any organization. 相似文献
11.
在科研项目管理过程中,项目负责人和其他成员组成了合作网络。本文检验了科研项目负责人网络位置对项目创新的影响,并分析了当合作网络的创新能力处于行业不同水平时,该影响是否存在差异。利用国家自然科学基金结题数据,结果表明,科研项目负责人的网络中心度对项目创新有正向影响,结构洞数对项目创新有倒U型影响。相比较合作网络创新能力处于行业高水平,当其处于中、低水平时,项目负责人网络位置对项目创新的影响更大。本研究结论不仅完善了网络位置对创新影响的相关文献,验证了我国提出项目负责人制进行项目管理的正确性,也对项目负责人制定管理方案有一定的指导意义。 相似文献
12.
[目的/意义]学术社交网络吸引了众多科研人员参与并使用,对学术社交网络中的学科交互研究有利于促进科研人员利用学术社交网络开展非正式交流及跨学科合作。[方法/过程]文章以ResearchGate(RG)为例,将iSchool成员机构作为研究对象,获取61所iSchool机构成员用户的交互关系数据,并对其中的2798所机构及其间所形成的30393条交互关系数据进行社会网络分析。[结果/结论]从交互数量来看,iSchool成员机构在学术社交网络中的学科交互范围较广,但跨学科影响力有限,其跨学科交互情况反映了目前图情学科领域的跨学科研究趋势和研究热点;从交互关系网络来看,iSchool成员机构整体学科交互关系网络结构较为松散,网络还呈现出iSchool成员机构分别主要与人文与社会科学类和工程与技术科学类的机构产生交互关系的两种趋势。此外,对学术社交网络中交互关系的拓展和学术影响力的提高有利于科研合作的开展和学术声望的提升。 相似文献
13.
在理论研究基础上,构建了创始人前摄性特质、社会网络与企业创新绩效之间的关系理论模型,运用多元回归分析方法,并通过对148份创新型企业问卷调查数据进行实证研究,探讨了社会网络对创新绩效的影响关系,以及社会网络在二者之间的中介作用机理。结果表明：社会网络均对创新绩效有显著正影响,且社会网络在前摄性与创新绩效之间起部分中介作用。此结论深化了对创始人前摄性特质、社会网络和创新绩效三者关系的理解,为企业在网络化发展模式中如何培养塑造创始人特质提供了理论参考。 相似文献
14.
《Information processing & management》2022,59(3):102917
Nowadays, signed network has become an important research topic because it can reflect more complex relationships in reality than traditional network, especially in social networks. However, most signed network methods that achieve excellent performance through structure information learning always neglect neutral links, which have unique information in social networks. At the same time, previous approach for neutral links cannot utilize the graph structure information, which has been proved to be useful in node embedding field. Thus, in this paper, we proposed the Signed Graph Convolutional Network with Neutral Links (NL-SGCN) to address the structure information learning problem of neutral links in signed network, which shed new insight on signed network embedding. In NL-SGCN, we learn two representations for each node in each layer from both inner character and outward attitude aspects and propagate their information by balance theory. Among these three types of links, information of neutral links will be limited propagated by the learned coefficient matrix. To verify the performance of the proposed model, we choose several classical datasets in this field to perform empirical experiment. The experimental result shows that NL-SGCN significantly outperforms the existing state-of-the-art baseline methods for link prediction in signed network with neutral links, which supports the efficacy of structure information learning in neutral links. 相似文献
15.
就引进型管理创新而言,获取已有创新知识,实现知识从组织外部向内部转移是关键.管理者所嵌入的社会网络通过提供广泛的多元化知识链接带来显著知识获取优势,促使管理者凭借网络影响力产生经济效益,从而成为管理创新知识获取的重要渠道.立足管理者个体社会网络视角,收集237家企业核心管理者的数据,通过多元回归分析,得出强连接优势显著,结构洞发挥实质作用,知识获取产生部分中介效应,社会网络、知识获取和管理创新引进水平之间整体影响关系成立等结论. 相似文献
16.
Lesly Alejandra Gonzalez Camacho Solange Nice Alves-Souza 《Information processing & management》2018,54(4):529-544
Recommender Systems are currently highly relevant for helping users deal with the information overload they suffer from the large volume of data on the web, and automatically suggest the most appropriate items that meet users needs. However, in cases in which a user is new to Recommender System, the system cannot recommend items that are relevant to her/him because of lack of previous information about the user and/or the user-item rating history that helps to determine the users preferences. This problem is known as cold-start, which remains open because it does not have a final solution. Social networks have been employed as a good source of information to determine users preferences to mitigate the cold-start problem. This paper presents the results of a Systematic Literature Review on Collaborative Filtering-based Recommender System that uses social network data to mitigate the cold-start problem. This Systematic Literature Review compiled the papers published between 2011–2017, to select the most recent studies in the area. Each selected paper was evaluated and classified according to the depth which social networks used to mitigate the cold-start problem. The final results show that there are several publications that use the information of the social networks within the Recommender System; however, few research papers currently use this data to mitigate the cold-start problem. 相似文献
17.
能有效预测在线社交网络中人的行为有较高的应用价值,对当前在线社交网络存在多种交互方式的现象进行分析,以此构建一种多维社交关系的在线社交网络链路预测的方法。基于社会影响和选择两种机制构建在线社交网络多维网络结构,综合各个维度节点和连边的拓扑结构,实现多维社交网络预测矩阵的集结,在降维后的网络上进行链路预测。利用百度贴吧数据集实验验证,从AUC和精确度两方面评价模型,结果表明本文提出的多维预测方法是有效的。 相似文献
18.
《International Journal of Information Management》2016,36(4):570-579
The purpose of this study is to empirically investigate the relationship between the social capital accumulated among network members and the performance of learning networks in terms of their ability to enhance knowledge sharing among network members. A network level perspective guided the sampling strategy adopted for this survey involving 150 members of 16 European learning networks. Hierarchical multiple regression and structural equation modelling were employed to investigate the inter-relationships between dimensions of social capital and knowledge sharing in learning networks. The results reveal that social interaction and cognitive social capital are positively and significantly related to knowledge sharing in learning networks. Social interaction is also shown to play an important role in the development of shared vision and shared language (i.e. cognitive social capital) in learning networks. This paper sheds further light on the inter-relationships between different dimensions of social capital from a network (rather than firm) level perspective, and contributes to emerging theory on the antecedents to, and assessment of, performance in learning network entities. 相似文献
19.
采用实证方法对组织文化与知识转移的关系进行了研究;采用虚拟的网络表示项目型组织的组织结构,并设计了实证与网络分析集成的模拟模型,对组织文化、结构、知识转移三者之间的相互作用进行模拟.研究结果表明分权、均匀的组织结构有利于知识转移和组织学习;组织结构与组织文化之间相互依存,成员对组织文化形成高度共识是组织内部非正式团队建设的基础. 相似文献
20.
Remedios Melero 《Biochemia medica : ?asopis Hrvatskoga dru?tva medicinskih biokemi?ara / HDMB》2015,25(2):152-160
Emerging metrics based on article-level does not exclude traditional metrics based on citations to the journal, but complements them. Both can be employed in conjunction to offer a richer picture of an article use from immediate to long terms. Article-level metrics (ALM) is the result of the aggregation of different data sources and the collection of content from multiple social network services. Sources used for the aggregation can be broken down into five categories: usage, captures, mentions, social media and citations. Data sources depend on the tool, but they include classic metrics indicators based on citations, academic social networks (Mendeley, CiteULike, Delicious) and social media (Facebook, Twitter, blogs, or Youtube, among others). Altmetrics is not synonymous with alternative metrics. Altmetrics are normally early available and allow to assess the social impact of scholarly outputs, almost at the real time. This paper overviews briefly the meaning of altmetrics and describes some of the existing tools used to apply this new metrics: Public Library of Science - Article-Level Metrics, Altmetric, Impactstory and Plum.Key words: altmetrics, article-level metrics, citation, social media 相似文献