网络信息计量学软件及其开发方向探讨

根据网络信息计量学的学科性质和研究内容，将支持网络信息计量研究的软件工具分为四大类：网络内容分析软件、网络结构分析软件、网站利用分析软件和数据处理软件；重点介绍CATPAC、TreeDec Tool、WebTrends Log Analyzer、Web－IAM 等四种软件，最后探讨网络信息计量学软件开发的趋势。     

国际学科教学知识的文献计量研究

学科教学知识(PCK)自舒尔曼1986年提出以来,受到了广泛关注。通过在Web of Science核心合集中对"PCK"进行文献计量研究,辅以CiteSpace进行关键词共现等分析,可以从整体上了解国际PCK的研究现状、研究热点与研究前沿问题。通过分析发现,在研究方法上,文献计量方法的综合使用有利于形成科学而准确的结论;在研究内容上,国际PCK的研究热点与研究前沿特征词较相似,体现了创新研究的不足。     

重庆五校土木类专业艺术教育现状调查研究

土木类专业实施艺术教育具有非常重要的意义。为了对土木类专业的艺术教育现状进行深入的分析和研究,进一步推进艺术教育的发展,采用问卷调查、访谈等方法,选取重庆市5所设有土木类专业的院校进行调查研究。结果显示,重庆市高校土木类专业的艺术教育在课程设置、艺术活动的开展、师资力量等方面都存在问题,限制了艺术教育的健康发展,最后提出了加强土木类专业艺术教育的对策与建议。     

Analysis of Academic Libraries' Facebook Posts: Text and Data Analytics

This research analyzed a dataset of academic libraries' posts on Facebook. It applied a text and data analytics approach to a dataset collected from the Facebook posts of academic libraries at the top 100 English-speaking universities, as listed by the 2014 Shanghai World University Rankings. The dataset is from a two-year posting history of 18,333 unique posts, 113,621 likes, and 3401 comments. Less than a quarter of the libraries had more than 2000 post-related likes, and only seven received more than 100 comments on their postings. Content analysis identified the most prevalent single word (unigrams), bigrams (two-word sequences), and trigrams (three-word sequences) in high and low engagement content. Semantic analysis identified the semantic categories for posts with high and low engagement. The findings can assist academic libraries in their social media strategies for engagement, marketing, and visibility.     

Research trends and collaborations by applied science researchers in South African universities of technology: 2007–2017

This paper analyses the publication patterns of researchers in the field of applied sciences at Universities of Technology in South Africa. Aspects investigated include publications in SCOPUS-listed journals; number of citations and countries of publication. Collaborative research patterns at national and international levels were also investigated. A bibliometric analysis approach was followed using SCOPUS as the main source of data and analysing the articles published in selected applied science disciplines. Results show that researchers in the field of applied sciences in universities of technology have increased their number of publications over the past 10?years and are also working in conjunction with other researchers both nationally and internationally. The analysis is an important addition to the field in South Africa which helps in measuring how institutions are positively responding to government incentives in research. The results are also important to information professionals who are increasingly playing an important role in research impact assessments.     

基于WoS数据库的馆际互借与文献传递研究综述

[目的/意义]整体把握馆际互借和文献传递发展脉络,探索馆际互借和文献传递的未来发展趋势。[方法/过程]以WoS核心合集作为统计源,采用文献计量学方法对国外馆际互借与文献传递研究文献的发文时间、国家与地区、机构与作者、发表刊物等进行统计分析;利用HisCite和CiteSpace筛选出重要相关文献,在对其进行阅读归纳的基础上,进行馆际互借研究的发展脉胳与主题分析。[结果/结论]馆际互借可分为传统馆际互借时期（20世纪80年代以前）、馆际互借研究迅速发展期（1980-1990年）、文献传递快速上升期（1990-2000年）、动态发展期（2000-2016年）4个阶段,未来馆际互借员角色应更加多样化。     

基于自引网络和主路径分析的论文主题创新实证研究

[目的/意义]探讨如何从大量论文中快速发现相关论文,研究论文主题创新的方法,为研究者阅读和利用期刊论文提供参考。[方法/过程]在对论文主题创新和自引网络概念界定的基础上,提出研究论文主题创新的思路、方法和工具。以美国印第安纳大学在图书情报学领域的论文为例进行实证研究。[结果/结论]利用主路径分析可以快速从自引网络中发现由于引用而产生联系的论文,在此基础上可以进行主题创新分析。     

Google Scholar's Coverage of the Engineering Literature 10 years Later

In 2008 Meier and Conkling first tested Google Scholar's coverage of the engineering literature against citations gathered from the Compendex database. Since that time, other studies have used the same methodology and found improvement in Google Scholar's coverage. This study uses engineering dissertations from Proquest Dissertations & Theses to create a data set of citations for the comparison of fee-based databases, Compendex and Scopus, against Google Scholar. From 1950 to 2017 Google Scholar outperformed both Compendex and Scopus in discoverability of citations in nine engineering subjects. These results have implications for collection management and information literacy program planning for librarians.     

Author ranking evaluation at scale

We evaluate author impact indicators and ranking algorithms on two publication databases using large test data sets of well-established researchers. The test data consists of (1) ACM fellowship and (2) various life-time achievement awards. We also evaluate different approaches of dividing credit of papers among co-authors and analyse the impact of self-citations. Furthermore, we evaluate different graph normalisation approaches for when PageRank is computed on author citation graphs.We find that PageRank outperforms citation counts in identifying well-established researchers. This holds true when PageRank is computed on author citation graphs but also when PageRank is computed on paper graphs and paper scores are divided among co-authors. In general, the best results are obtained when co-authors receive an equal share of a paper's score, independent of which impact indicator is used to compute paper scores. The results also show that removing author self-citations improves the results of most ranking metrics. Lastly, we find that it is more important to personalise the PageRank algorithm appropriately on the paper level than deciding whether to include or exclude self-citations. However, on the author level, we find that author graph normalisation is more important than personalisation.     

The more multidisciplinary the better? – The prevalence and interdisciplinarity of research collaborations in multidisciplinary institutions

Scientific research is increasingly relying on collaborations to address complex real-world problems. Many researchers, policymakers, and administrators consider a multidisciplinary environment an important factor for fostering research collaborations, especially interdisciplinary ones that involve researchers from different disciplines. However, it remains unknown whether a higher level of multidisciplinarity within an academic institution is associated with internal collaborations that are more prevalent and more interdisciplinary. Analyzing 90,000 publications by 2500 faculty members in over 100 academic institutions from three multidisciplinary areas, information, public policy, and neuroscience, we investigated the connection between multidisciplinarity and research collaborations. Based on social network analysis and text mining, our analysis suggests that more multidisciplinary institutions are not necessarily more collaborative, although they do feature collaborations that are more interdisciplinary. Our findings provide implications for academic administrators and policymakers to promote research collaborations and interdisciplinarity in academic institutions.