Altmetrics – a complement to conventional metrics

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     

Ranking themes on co-word networks: Exploring the relationships among different metrics

As network analysis methods prevail, more metrics are applied to co-word networks to reveal hot topics in a field. However, few studies have examined the relationships among these metrics. To bridge this gap, this study explores the relationships among different ranking metrics, including one frequency-based and six network-based metrics, in order to understand the impact of network structural features on ranking themes on co-word networks. We collected bibliographic data from three disciplines from Web of Science (WoS), and generated 40 simulation networks following the preferential attachment assumption. Correlation analysis on the empirical and simulated networks shows strong relationships among the metrics. Their relationships are consistent across disciplines. The metrics can be categorized into three groups according to the strength of their correlations, where Degree Centrality, H-index, and Coreness are in one group, Betweenness Centrality, Clustering Coefficient, and frequency in another, and Weighted PageRank by itself. Regression analysis on the simulation networks reveals that network topology properties, such as connectivity, sparsity, and aggregation, influence the relationships among selected metrics. In addition, when comparing the top keywords ranked by the metrics in the three disciplines, we found the metrics exhibit different discriminative capacity. Coreness and H-index may be better suited for categorizing keywords rather than ranking keywords. Findings from this study contribute to a better understanding of the relationships among different metrics and provide guidance for using them effectively in different contexts.     

Measuring the impact of spammers on e-mail and Twitter networks

This paper investigates the research question if senders of large amounts of irrelevant or unsolicited information – commonly called “spammers” – distort the network structure of social networks. Two large social networks are analyzed, the first extracted from the Twitter discourse about a big telecommunication company, and the second obtained from three years of email communication of 200 managers working for a large multinational company. This work compares network robustness and the stability of centrality and interaction metrics, as well as the use of language, after removing spammers and the most and least connected nodes. The results show that spammers do not significantly alter the structure of the information-carrying network, for most of the social indicators. The authors additionally investigate the correlation between e-mail subject line and content by tracking language sentiment, emotionality, and complexity, addressing the cases where collecting email bodies is not permitted for privacy reasons. The findings extend the research about robustness and stability of social networks metrics, after the application of graph simplification strategies. The results have practical implication for network analysts and for those company managers who rely on network analytics (applied to company emails and social media data) to support their decision-making processes.     

不同学科领域期刊Citescore指标与其影响因子、特征因子的相关性分析

[目的/意义] Citescore是Elsevier发布的一个新的学术期刊评价指标,研究Citescore指标的主要特点和它在学术期刊评价中发挥的效力,对于发展和完善学术期刊评价是至关重要的。[方法/过程] 本文以自然科学和社会学科领域的期刊为研究对象,对这些期刊的Citescore指标与其对应的影响因子、特征因子进行了相关性分析,并讨论Citescore指标的主要特征以及它与影响因子、特征因子的关联和差异。[结果/结论] 研究结果表明,相对于影响因子和特征因子,Citescore指标在源引数据库、引证时间、文献类型、计算透明度以及免费获取方面具有明显的优势。同时,研究结果也表明,期刊的Citescore指标与其影响因子的相关性高于Citescore指标与其特征因子的相关性,而且期刊的Citescore指标与其影响因子、特征因子的相关性依赖于学科领域。     

How journal rankings can suppress interdisciplinary research: A comparison between Innovation Studies and Business & Management

This study provides quantitative evidence on how the use of journal rankings can disadvantage interdisciplinary research in research evaluations. Using publication and citation data, it compares the degree of interdisciplinarity and the research performance of a number of Innovation Studies units with that of leading Business & Management Schools (BMS) in the UK. On the basis of various mappings and metrics, this study shows that: (i) Innovation Studies units are consistently more interdisciplinary in their research than Business & Management Schools; (ii) the top journals in the Association of Business Schools’ rankings span a less diverse set of disciplines than lower-ranked journals; (iii) this results in a more favourable assessment of the performance of Business & Management Schools, which are more disciplinary-focused. This citation-based analysis challenges the journal ranking-based assessment. In short, the investigation illustrates how ostensibly ‘excellence-based’ journal rankings exhibit a systematic bias in favour of mono-disciplinary research. The paper concludes with a discussion of implications of these phenomena, in particular how the bias is likely to affect negatively the evaluation and associated financial resourcing of interdisciplinary research organisations, and may result in researchers becoming more compliant with disciplinary authority over time.     

基于最可几值的学科期刊影响因子的讨论

在分析多学科期刊影响因子分布特征的基础上,引入学科期刊最可几影响因子表征学科期刊整体的影响因子水平,并使用对数正态分布函数表征学科期刊影响因子的分布形状,利用对数正态分布函数的特征参数表达学科期刊平均影响因子水平与分布宽度。最后,提出学科最可几期刊影响因子加上相应对数正态分布函数的特征参数可以表征学科期刊整体影响因子水平的观点。     

期刊论文网络下载规律及与引文指标相关性研究

对期刊论文网络下载研究作了简要回顾,从期刊论文被引频次分布规律研究得到启示,以《中国学术期刊网络出版总库》为统计源,通过大样本抽样统计分析,结果表明:期刊论文网络下载频次分布均遵循负对数函数衰减,衰减速率由最高下载频次、篇均下载频次与载文量三个因素决定,并拟合出经验模型;期刊论文的网络下载频次与被引频次之间的线性相关性不稳定,不同期刊的差异较大,但总体上表现为显著的(中等)线性相关关系.从期刊层次考察,不同期刊的网络总下载量与总被引量为高度线性相关,网络篇均下载量与篇均被引量的线性相关性更强.     

Co-authorship networks in the digital library research community

The field of digital libraries (DLs) coalesced in 1994: the first digital library conferences were held that year, awareness of the World Wide Web was accelerating, and the National Science Foundation awarded $24 Million (US) for the Digital Library Initiative (DLI). In this paper we examine the state of the DL domain after a decade of activity by applying social network analysis to the co-authorship network of the past ACM, IEEE, and joint ACM/IEEE digital library conferences. We base our analysis on a common binary undirectional network model to represent the co-authorship network, and from it we extract several established network measures. We also introduce a weighted directional network model to represent the co-authorship network, for which we define AuthorRank as an indicator of the impact of an individual author in the network. The results are validated against conference program committee members in the same period. The results show clear advantages of PageRank and AuthorRank over degree, closeness and betweenness centrality metrics. We also investigate the amount and nature of international participation in Joint Conference on Digital Libraries (JCDL).     

创始人前摄性特质对企业创新绩效的影响：社会网络的中介作用

 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。     

The social networks of collaborative process

We present a study exploring the connection between social networks and collaborative process. We focus on exploring academics' network position and its effect on their collaborative networks. In this paper, we discuss two types of networks of collaboration—(i) citation; and, (ii) co authorship. We explore the effects of social networks on these two types of collaborative process. By defining network position in this way, we develop a social network that uses the academics as nodes within the network instead of each published paper. We obtained the collaboration data through archival records (i.e. Web of Science) and examined the interactions among different actors from the archival records for determining the existence and strength of relations between actors.     

国际期刊评价指标的实证分析——基于WOS和Scopus数据库对比视角

以Web of Science(WOS)数据库JCR中的眼科学期刊(OPHTHALMOLOGY)为研究对象,采用SPSS21.0统计学软件比较基于Scopus数据库的评价指标SNIP、SJR、H指数与JCR收录期刊的IF之间的相关性,从而分析Scopus数据库、WOS数据库评价期刊是否存在一致性,SNIP和IF(JCR)评价眼科学期刊是否有差异性。结果显示,期刊评价指标SJR、SNIP、H指数、IF(JCR)之间显著相关,由此说明Scopus数据库评价期刊是可行的,两种数据库评价期刊一致性较好;在眼科学领域,Scopus数据库中SNIP指标与IF(JCR)存在一定的差异性,经统计学分析显示差异不显著。     

国内电子资源研究文献的计量学分析

利用中国知网学术期刊文献库为数据源,统计截止2010年我国发表的电子资源研究论文,对其论文发表年代、期刊分布、基金论文分布、作者合著情况、作者机构分布、研究主题、下载频次、被引频次等多角度进行全面的统计分析,综合评述我国电子资源研究的主题热点及发展趋势,同时针对电子资源建设现阶段存在问题为其未来发展研究提出意见和建议。     

国际权威图情期刊不同类型NCD的施引与被引特征实证分析

以SSCI(社会科学引文索引)收录的信息科学和图书馆学期刊为范围,在2年影响因子时间窗口内,实证分析非可被引文献(Non-citable Document,NCD)的引证特征。结果发现,信息科学和图书馆学期刊发文数量、被引频次百分比较高的NCD类型是述评、信稿,2种文献引证效率也较高;NCD不仅可被引而且还对文献进行施引,NCD的被引量和NCD对可被引文献引用的引用量在影响因子被引量中占很大一部分;部分期刊NCD对影响因子的贡献率不容忽视。本研究有利于国内信息科学与图书馆学领域科研工作人员了解国际相关领域期刊的文献特征,有意识调整办刊方式、办刊理念和办刊技巧,加强选题策划,提升期刊影响力。     

压力分析框架下移动社交网络用户间歇性中辍的影响因素与形成机理

[目的/意义]探究诱发移动社交网络用户间歇性中辍行为的关键因素及其相互作用机理,为移动社交网络的设计者、开发者和运营者的社交网络功能优化、信息服务质量提升和精准营销推广等实践工作提供可供参考的意见和建议。[方法/过程]以"压力源-压力-结果"为分析框架,在整合压力应对理论、使用与满足理论和社会支持理论的基础上,从技术压力和使用满足的视角出发提出研究假设构建研究模型。实证研究以微信的深度用户为研究样本,采用"情境实验+问卷访谈"的方式获取404份有效样本数据,利用Smart PLS2.0软件验证假设和模型。[结果/结论]技术压力和使用满足的影响在用户使用社交网络时同时存在,均能显著正向影响用户的产品转换疲劳和使用疲劳,两者的综合作用能诱发用户间歇性中辍行为。其中,技术压力因素中的信息过载、功能过载是产生社交网络使用疲劳的重要前因;使用满足因素中的情感需要满足、社交需要满足和信息需要满足是产生社交网络转换疲劳的重要前因。     

基于用户行为感知的移动社交网络信息服务持续使用意愿研究

[目的/意义]本文以用户行为感知视角，研究影响移动社交网络主导型用户与浏览型用户持续使用的因素，为移动社交网络信息服务提供理论基础，并为移动社交网络提供商提出参考与应用借鉴。[方法/过程]分析移动社交网络主导型用户与浏览型用户持续使用意愿影响因素，引入相关变量，构建了基于用户行为感知的移动社交网络信息服务持续使用意愿模型并提出假设，最后通过结构方程模型进行实证分析。[结果/结论]感知有用性、感知易用性、感知娱乐、感知质量等因素均显著影响主导型及浏览型两类用户；服务质量、感知风险、知识获取、个人创新、社会认可、感知信任、感知转换成本等因素对两类用户有不同程度的影响。     

Estimating Business and Management journal quality from the 2008 Research Assessment Exercise in the UK

The 2008 Research Assessment Exercise in the UK involved the peer review of over 12,500 research outputs in Business and Management, of which 92% were journal articles. Each output was graded on a 4-point scale from “world leading” to “national” with a fifth point being unclassified. These grades were accumulated for each department to provide an overall quality profile in terms of the proportions of its outputs in each category. The assessments of individual papers were not made public but the papers submitted by each department were. This data provides a major opportunity for addressing issues of concern about the evaluation of research and the effects of journal rankings, as well as the possibility of reconstructing the judgements made by the Panel about journal quality. Given the submission details and the resulting grade profile for each department, we have used linear programming to produce the best estimate of the grades awarded to papers from each journal that had more than three entries. This provides both a grade profile for each journal and a single quality estimate. The results are shown to have good validity in comparison with other journal rankings. Apart from providing a ranking of 700 journals based on the RAE results, the paper is also able to shed light on issues such as the accuracy and coverage of the ABS ranking; the degree of selectivity of submissions; the dispersion of grades for a journal; and differences between different subject areas.     

中国科技期刊的学术质量折射出管理政策需要改善——基于中国SCI期刊群学术影响力年间变动的统计学分析

为确定中国科技期刊学术影响力的变化,取用ISI JCR中的数据,选用被JCR收录的中国（大陆）科技期刊作为中国科技期刊的代表,用One-Way ANOVA统计学技术,对2002—2008年间的期刊学术影响力进行了分析。学术影响力定义为目标期刊的影响因子与该领域期刊影响因子平均值的比值。研究发现,中国SCI期刊群2002—2008年间的学术影响力没有变化。本研究提示,要提升中国科技期刊的国际学术地位,有关管理政策亟待改善。     

社会资本对科学家科研绩效的影响研究

本文从结构维、认知维和关系维出发,研究科研合作网络中的社会资本对科学家科研绩效的影响。我们从web of science上收集了化学领域26.74万篇论文,基于这些论文作者合作数据构建了科学家合作网络,并从上述三个方面对其中的社会资本进行了测度。研究结果显示,认知维社会资本和关系维社会资本在一定程度上对科研绩效具有显著的促进作用,而结构维社会资本对科研人员的科研绩效具有显著的非线性关系。本文为建立积极有效的科研合作网络,高效利用合作网络中的社会资本为科学家更好地开展科研活动提供了一定借鉴。     

Using the h-index to measure the quality of journals in the field of business and management

This paper considers the use of the h-index as a measure of a journal’s research quality and contribution. We study a sample of 455 journals in business and management all of which are included in the ISI Web of Science (WoS) and the Association of Business School’s peer review journal ranking list. The h-index is compared with both the traditional impact factors, and with the peer review judgements. We also consider two sources of citation data – the WoS itself and Google Scholar. The conclusions are that the h-index is preferable to the impact factor for a variety of reasons, especially the selective coverage of the impact factor and the fact that it disadvantages journals that publish many papers. Google Scholar is also preferred to WoS as a data source. However, the paper notes that it is not sufficient to use any single metric to properly evaluate research achievements.     

A new perspective to automatically rank scientific conferences using digital libraries

Citation analysis is performed in order to evaluate authors and scientific collections, such as journals and conference proceedings. Currently, two major systems exist that perform citation analysis: Science Citation Index (SCI) by the Institute for Scientific Information (ISI) and CiteSeer by the NEC Research Institute. The SCI, mostly a manual system up until recently, is based on the notion of the ISI Impact Factor, which has been used extensively for citation analysis purposes. On the other hand the CiteSeer system is an automatically built digital library using agents technology, also based on the notion of ISI Impact Factor. In this paper, we investigate new alternative notions besides the ISI impact factor, in order to provide a novel approach aiming at ranking scientific collections. Furthermore, we present a web-based system that has been built by extracting data from the Databases and Logic Programming (DBLP) website of the University of Trier. Our system, by using the new citation metrics, emerges as a useful tool for ranking scientific collections. In this respect, some first remarks are presented, e.g. on ranking conferences related to databases.