Mining diversity subgraph in multidisciplinary scientific collaboration networks: A meso perspective

This paper proposes a framework to analyze the interdisciplinary collaboration in a coauthorship network from a meso perspective using topic modeling: (1) a customized topic model is developed to capture and formalize the interdisciplinary feature; and (2) the two algorithms Diversity Subgraph Extraction (DSE) and Constraint-based Diversity Subgraph Extraction (CDSE) are designed and implemented to extract a meso view, i.e. a diversity subgraph of the interdisciplinary collaboration. The proposed framework is demonstrated using a coauthorship network in the field of computer science. A comparison between DSE and Breadth First Search (BSF)-based subgraph extraction favors DSE in capturing the diversity in interdisciplinary collaboration. Potential possibilities for studying various research topics based on the proposed framework of analysis are discussed.     

我国图书馆、情报与文献学领域作者合作现状——基于小世界理论的分析

本文以2002年至2006年五年间CSSCI收录的图书馆、情报与文献学期刊论文作者为数据源,分析了各年作者合作率趋势、期刊作者合作率分布等作者合作特征,总结出该领域作者合作的现状;并建立了作者合作网络,析出了最大连通图,计算出该图的平均路径以及聚类系数,发现该作者合作网络具有小世界效应,为小世界网络.并通过与物理学、生物学以及数学作者合作网络比较,讨论了不同学科之间的作者合作的特征.     

A regression analysis of researchers’ social network metrics on their citation performance in a college of engineering

Previous research shows that researchers’ social network metrics obtained from a collaborative output network (e.g., joint publications or co-authorship network) impact their performance determined by g-index. We use a richer dataset to show that a scholar's performance should be considered with respect to position in multiple networks. Previous research using only the network of researchers’ joint publications shows that a researcher's distinct connections to other researchers, a researcher's number of repeated collaborative outputs, and a researchers’ redundant connections to a group of researchers who are themselves well-connected has a positive impact on the researchers’ performance, while a researcher's tendency to connect with other researchers who are themselves well-connected (i.e., eigenvector centrality) had a negative impact on the researchers’ performance. Our findings are similar except that we find that eigenvector centrality has a positive impact on the performance of scholars. Moreover, our results demonstrate that a researcher's tendency toward dense local neighborhoods and the researchers’ demographic attributes such as gender should also be considered when investigating the impact of the social network metrics on the performance of researchers.     

Patterns of Iranian co-authorship networks in social sciences: A comparative study

Collaboration in science is a process in which two or more authors share their ideas, resources and data to create a joint work. This research compares coauthorship networks of Iranian articles in library and information science (LIS), psychology (PSY), management (MNG), and economics (ECO) in the ISI Web of Knowledge database during 2000–2009, and uses network analysis for the visualization of coauthorship networks. Data include all articles with at least one Iranian author and indexed in ISI's Social Science Citation Index (SSCI) for the fields of LIS, PSY, MNG, and ECO. Indicators such as the Collaborative Index (CI), Degree of Collaboration (DC) and Collaboration Coefficient (CC) were calculated for each discipline. Results show that two or three authors were the most common number of authors per paper, and authors of PSY tended to have more multi-authored articles, compared to the other disciplines. LIS had the lowest rank regarding CC. MNG had the densest coauthorship network, and PSY had the sparsest. Iranian authors in the field of PSY mostly collaborated with those in the U.S., while LIS and MNG authors tended to collaborate with U.K. authors, and ECO authors tended to collaborate with Canadians.     

Measuring contextual partner importance in scientific collaboration networks

Scientific collaboration commonly takes place in a global and competitive environment. Coalitions and consortia are formed among universities, companies and research institutes to apply for research grants and to perform joint projects. In such a competitive environment, individual institutes may be strategic partners or competitors. Measures to determine partner importance have practical applications such as comparison and rating of competitors, reputation evaluation or performance evaluation of companies and institutes. Many network-centric metrics exist to measure the important of individuals or companies in social and collaborative networks. Here we present a novel context-based metric to measure the importance of partners in scientific collaboration networks. Well-established graph models such as the notion of hubs and authorities provide the basis for this work and are systematically extended to a flexible, context-aware network importance measure.     

链接分析领域的作者合作网络及其分析

本文回顾了复杂网络中的科研合作网络在情报学领域的研究成果,详细分析了部分网络参数的情报学意义。其次,构建了基于Web of Science数据库的1998年1月至2008年1月链接分析领域的作者合作网络,运用复杂网络理论以及社会网络分析法,对作者合作网络进行了详细的分析,得出了链接分析领域合作的一些特性。最后,提出了有待进一步解决的问题。以期探索和推进复杂网络在情报学领域的实际应用。     

Social media-based sleeping beauties: Defining,identifying and features

The sleeping beauties in science signify a unique knowledge diffusion trajectory created by citation after the publication of scientific literature. However, in social media, scientific knowledge creates a new diffusion trajectory through social media metrics such as View, Save, Discussed, and Recommendations. This study aims to define social media–based sleeping beauties S-SB in science by using social media metrics which we termed as citation-based Sleeping Beauties in science, C-SB. We constructed a quantitative method to identify S-SB and conducted an empirical study of all types of 4019 articles published in PLOS Biology. Comparison of the S-SB and C-SB results revealed that from the perspective of social media metrics, C-SB has become the literature of S-total elements early gradual awakening type, S-total elements delay gradual awakening type, and S-early sudden awakening type. Moreover, the awakening time of C-SB literature under the action of social media metrics was found to be 4–5 years earlier than that under the action of citation-based indicators. Both C-SB and S-SB included significant “Editorial Material,” establishing that “Editorial Material” type literature is noteworthy while promoting the diffusion of scientific knowledge. Overall, this study extends the perspective of sleeping beauties in science.     

Exploring the influence of coauthorship with top scientists on researchers’ affiliation,research topic,productivity, and impact

Research studies have found that coauthorship with top scientists positively correlates with researchers’ career advancement. However, the influence of different proximities and types of coauthorship with top scientists on their performance has rarely been discussed. We identified the winners of four awards as top authors. We also evaluated the effect on the researchers’ affiliation change, research topic, productivity, and impact before and after three top-ordinary scientist coauthorship types (strong, moderate, and weak), examining the effect after top-top and ordinary-ordinary scientist coauthorships. Additionally, a coauthorship closeness indicator was proposed, considering the team size and author role to measure the collaboration relationship between coauthors. The results reveal that the top scientist in strong coauthorship obtained the highest affiliation change rate. For the top-ordinary coauthorship, the affiliation change rate for top scientists is higher than for ordinary scientists. For other aspects (the coauthor number, research topic, productivity, and impact), the rate after strong and moderate coauthorships increases compared to weak top-ordinary coauthorship type for top and ordinary scientists. Therefore, top scientists obtain a partner with skills, and ordinary scientists obtain more guidance. Strong and moderate coauthorships are win-win relationships for top-ordinary coauthorship types.     

Disruptive coefficient and 2-step disruptive coefficient: Novel measures for identifying vital nodes in complex networks

The identification and ranking of vital nodes in complex networks have been a critical issue for a long time. In this paper, we present an extension of existing disruptive metrics and introduce new ones, namely the disruptive coefficient (D) and 2-step disruptive coefficient (2-step D), as innovative tools for identifying critical nodes in complex networks. Our approach emphasizes the importance of disruptiveness in characterizing nodes within the network and detecting their criticality. Our new measures take into account both prior and posterior information of the focal nodes, by evaluating their ability to disrupt the previous network paradigm, setting them apart from traditional measures. We conduct an empirical analysis of four real-world networks to compare the rankings or identification of nodes using D and 2stepD with those obtained from four renowned benchmark measures, namely, degree, h-index, PageRank, and the CD index. Our analysis reveals significant differences between the nodes identified by D and 2stepD and those identified by the benchmark measures. We also examine the correlation coefficient and efficiency of the metrics and find that D and 2stepD have significant correlations with the CD index, but have weak correlations with the benchmark measures. Furthermore, we show that D and 2stepD outperform CD index and random ways in intentional attacks. We find power law distributions for D, 2stepD, and CD, indicating a small number of highly disruptive nodes and a large number of less disruptive nodes in the networks. Our results suggest that D and 2stepD are capable of providing valuable and distinct insights for identifying critical nodes in complex networks.     

我国图书情报学领域机构合作网络分析

科研合作是促进科学生产的一种重要形式,探讨不同机构之间的科研论文合著情况,可以有效把握机构合作的整体现状与特征,有助于提高机构合作的绩效。本研究基于2010-2015 年Web of Science 数据库图书情报学领域期刊发表的论文,构建我国图书情报学领域Top15 高产研究机构的合作网络,综合运用文献合著率、合作多样性、合作稳定度、合作绩效等度量指标,分析了机构合作的主要特征及指标间的相互影响。研究发现：我国图书情报学领域的论文数量总体上呈现增长趋势但论文影响力相对有限,香港地区的科研机构在国际上学术认可度领先于大陆地区的科研机构;科研机构间的合作对象不断拓宽、合作密度不断加强、合作论文产出不断提升成为我国近年来图书情报学领域发展的显著特征;国际化的合作团队、多元的合作对象和稳定的合作关系可以为科研机构带来更多的科研成果产出,提高其学术影响力。     

On the relationship between the structural and socioacademic communities of a coauthorship network

This article presents a study that compares detected structural communities in a coauthorship network to the socioacademic characteristics of the scholars that compose the network. The coauthorship network was created from the bibliographic record of a multi-institution, interdisciplinary research group focused on the study of sensor networks and wireless communication. Four different community detection algorithms were employed to assign a structural community to each scholar in the network: leading eigenvector, walktrap, edge betweenness and spinglass. Socioacademic characteristics were gathered from the scholars and include such information as their academic department, academic affiliation, country of origin, and academic position. A Pearson’s χ²test, with a simulated Monte Carlo, revealed that structural communities best represent groupings of individuals working in the same academic department and at the same institution. A generalization of this result suggests that, even in interdisciplinary, multi-institutional research groups, coauthorship is primarily driven by departmental and institutional affiliation.     

基于CSCD和SCI的跨省区科学合作网络可视化分析

利用CSCD（1998-2005）和SCI（2000-2005）数据库得出我国31个省区科学合作论文的数据矩阵，构建出一系列跨省区、有向加权的合作网络。利用网络绘图分析软件Netdraw将其可视化，并从不同角度将省区间的科学合作状态表现出来并加以分析。结果显示：弱势省区倾向于与强势省区合作；弱势省区之间合作极少；SCI合作网络中各省区之间的合作差异程度大于CSCD合作网络中的合作差异程度。     

Total influence and mainstream measures for scientific researchers

We propose two new indices that are able to measure a scientific researcher's overall influence and the level of his/her works’ association with the mainstream research subjects within a scientific field. These two new measures – the total influence index and the mainstream index – differ from traditional performance measures such as the simple citation count and the h-index in that they take into account the indirect influence of an author's work. Indirect influence describes a scientific publication's impact upon subsequent works that do not reference it directly. The two measures capture indirect influence information from the knowledge emanating paths embedded in the citation network of a target scientific field. We take the Hirsch index, data envelopment analysis, and lithium iron phosphate battery technology field to examine the characteristics of these two measures. The results show that the total influence index favors earlier researchers and successfully highlights those researchers who have made crucial contributions to the target scientific field. The mainstream index, in addition to underlining total influence, also spotlights active researchers who enter into a scientific field in a later development stage. In summary, these two new measures are valuable complements to traditional scientific performance measures.     

Error and attack tolerance of small-worldness in complex networks

Complex networks may undergo random and/or systematic failures in some of their components, i.e. nodes and edges. These failures may influence various network properties. In this article, for a number of real-world as well as Watts–Strogatz model networks, we investigated the profile of the network small-worldness as random failures, i.e. errors, or systematic failures, i.e. attacks, occurred in the nodes. In errors nodes are randomly removed along with all their tipping edges, while in attacks the nodes with highest degrees are removed from the network. Interestingly, in many cases, the small-worldness of violated networks increased as more nodes underwent an attack. This indicates an important role of the hub nodes in controlling the small-worldness of Watts–Strogatz networks. The profile of changes in the small-worldness as a result of errors/attacks was independent of network size, while it was influenced by average degree and rewiring probability of Watts–Strogatz model. We also found that the pattern of the changes of the small-worldness in real-world networks is completely different than that of the Watts–Strogatz networks. Therefore, although Watts–Strogatz model is often used for constructing networks with small-world property, the resulting networks have different properties compared to real-world ones in terms of robustness in the small-worldness index against errors/attacks.     

社会网络在开放式知识创新中的应用价值研究

通过对关于社会网络、知识创新和开放式创新相关文献进行回顾,试图探索社会网络的不同类型、社会资本的不同维度如何影响知识创新。分析结果显示出社会网络不同因素与其成员创造知识的能力之间存在复杂关系。研究结果表明密集型网络中的知识类型趋向于同质性,而松散型网络中的知识类型趋向于异质性。针对不同类型的网络结构提出开放式知识创新策略。最后,设计社会网络中开放式知识创新的模型。     

Personal ties,group ties and latent ties: connecting network size to diversity and trust in the mobile social network WeChat

This study examines whether and how network size is associated with diversity and trust in the mobile SNS context. Online survey data (N?=?327) on Chinese WeChat users reveal that both personal network size and extended network size are positively related to the diversity of people’s social networks. We believe the explanation for these findings may be that the affordances of WeChat provide users opportunities to accumulate a wide spectrum of relations ranging from strong ties, weak ties to latent ties and thus a larger network can enable them to access to more diverse resources. We also find that extended network size is negatively related to people’s trust in their WeChat contacts. We argue that the increasing size of the extended network may reduce familiarity, certainty and accountability that assumed to be prerequisites of trust.     

基于Twitter关注度的期刊影响力评价指标——以国际图书情报学顶级期刊为例

[目的/意义] 随着社交媒体和电子出版平台的兴起,利用期刊在Twitter上的关注度来评价期刊能够对传统的期刊评价方式进行补充,发现该指标与传统指标之间的相关性关系,并以期最终构建合理的期刊社交网络影响力评价指标。[方法/过程] 根据《期刊引用报告》(Journal Citation Reports,JCR)的社会科学版,选取国际图书情报学领域影响因子前30位的期刊作为该领域的国际顶级期刊。为了研究altmetrics指标与传统的基于引文的评价指标间的相关关系,利用Spearman非参数相关性分析对期刊Twitter提及频次与8个传统指标(总被引数、影响因子、5年期影响因子、即年指标、论文数、引文半衰期、特征因子和论文影响分值)之间的相关性进行分析。[结果/结论] 统计结果显示,JASIST、College & Research Libraries和Scientometrics是本领域中在Twitter上受关注度最高的期刊。期刊Twitter提及频次仅与期刊特征因子间存在中等的显著相关性,与其他指标间存在较弱的相关性。值得注意的是,相比其他期刊,在Twitter上设有官方账号的期刊明显得到更高的关注度。     

从社区到社会网络——一种互联网研究视野与方法的拓展

随着互联网技术的发展,传统的BBS等虚拟社区的影响有所减弱,而由SNS、即时通信、博客等应用构建的新兴社区的影响正在上升,这些新的应用也促进了人们的社会网络的形成与拓展。借鉴社会学的社会网络理论来研究这些新的应用及其影响,是十分必要的。人们从传统虚拟社区向以自我为中心的社会网络的迁移,体现了网络使用者从社会归属需求向社会资本需求的升级,而印象管理、自我表达、情绪调节、社会交往、社会分享、社会参与等其他层面需求则与社会资本需求相辅相成。互联网上的社会网络对于个体的影响,目前主要在两个方面表现出来:一方面是一对一的互动对个体的态度、行为的影响(这些影响可以从社会心理学的一些传统理论中得到解释),而这种一对一的影响还可能通过社会网络来传递,从而形成一种社会性影响;另一方面是社会网络的结构对个体所施加的影响,例如,社会网络中的权力关系的影响、社会网络中的派系的影响等。     

科研合作网络弹性研究与实证

阐述科研合作网络弹性的概念、研究意义与应用,并以全球100所高校在图书情报学领域所组成的科研合作网络为例,选取网络最大簇规模和网络效率作为网络弹性测度指标,讨论节点点度失效、介数失效以及随机失效策略下该科研合作网络的弹性。结果显示,科研合作网络对随机节点失效具有较强的鲁棒性,其网络容错能力较强;对选择性节点失效的网络抗攻击能力较弱;网络效率相对于网络最大簇规模更适合作为科研合作网络弹性的测度指标。     

Re-presenting Sport: How Instant Replay and Perceived Violence Impact Enjoyment of Mediated Sports

Several long-standing theories intersect in discussing the impact of community characteristics and of the mass media. The structural pluralism model popularized by Tichenor and his colleagues says that social structure influences how mass media operate in communities because they respond to how power is distributed in the social system, whereas the linear model says that the increasing size of a community's population leads to more social differentiation and diversity and corresponding increases in subcultures with their own beliefs, customs, and behaviors. Recently, there has been a concern about how changes in society have led to a decline in organizational activity and the network of relationships and trust that constitute “social capital.” This article examines the impact of population and diversity (using census data) on individuals’ media use, interpersonal discussion and civic engagement (measured in a national survey), and the relationship among these variables. Analysis of a structural model provides evidence that the “linear hypothesis” can be combined with structural pluralism, with size—measured by population—impacting diversity, which influences the relationships that people have with their community. Concurrently, social categories influence people's communication patterns and community relationships, and communication impacts civic engagement.