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Analyzing Social Media Networks with NodeXL offers backgrounds in information studies, computer science, and sociology.This book is divided into three parts: analyzing social media, NodeXL tutorial, and social-media network analysis case studies.Part I provides background in the history and concepts of social media and social networks.

PurposeThis study demonstrates that aggregated data from the Repository Analytics and Metrics Portal (RAMP) have significant potential to analyze visibility and use of institutional repositories (IR) as well as potential factors affecting their use, including repository size, platform, content, device and global location. The RAMP dataset is unique and public.Design/methodology/approachThe webometrics methodology was followed to aggregate and analyze use and performance data from 35 institutional repositories in seven countries that were registered with the RAMP for a five-month period in 2019. The RAMP aggregates Google Search Console (GSC) data to show IR items that surfaced in search results from all Google properties.FindingsThe analyses demonstrate large performance variances across IR as well as low overall use. The findings also show that device use affects search behavior, that different content types such as electronic thesis and dissertation (ETD) may affect use and that searches originating in the Global South show much higher use of mobile devices than in the Global North.Research limitations/implicationsThe RAMP relies on GSC as its sole data source, resulting in somewhat conservative overall numbers. However, the data are also expected to be as robot free as can be hoped.Originality/valueThis may be the first analysis of aggregate use and performance data derived from a global set of IR, using an openly published dataset. RAMP data offer significant research potential with regard to quantifying and characterizing variances in the discoverability and use of IR content.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-08-2020-0328

Another common strategy for evaluating research schemes is to assess the number and citation impact of the project outputs. This has the advantage of being transparent, independent and giving results that can be compared to bibliometric benchmarks or between schemes and funding agencies, if appropriately normalised.

Purpose This study aims to design a proposed framework for evaluating university websites. Design/methodology/approach This study is an exploratory mixed research. It was an applied research in terms of objective and used the Delphi technique and systematic review and meta-analysis approaches. Data collection tools were done through library studies, Delphi checklist and observation. The statistical population of the research comprised 17 experts who are designers of university websites and 20 Iranian university websites selected from the Webometrics website. The statistical data were analyzed using fuzzy methods, descriptive and inferential statistical methods and the SWARA weighting method. Also, the statistical analysis software SPSS 20 and Excel 2016, TOPSIS engineering software and MAXQDA were used. Findings Findings indicated that the dimensions of the designed proposed framework in order of their weights are credibility (0.130), reliability (0.125), usability (0.120), website design (0.110), functionality (0.104), content (0.100), page design (0.0922), efficiency (0.082), Webometrics (0.070) and systematic evaluation (0.067). Mebrate’s (2010) framework had the highest overlap (mean = 74.65), and Webometrics (mean = 18.5) had the least overlap and dependency (mean = 19) with the proposed framework. In the evaluation of the 20 university websites of Iran selected from the Webometrics site, the University of Tehran was ranked first with a score of 82.7 and Shiraz University was ranked last with a score of 75. Originality/value This study provides a comprehensive proposed framework for evaluating university websites that eliminates the shortcomings of all models, frameworks and methods of university website evaluation that focused only on one or more dimensions of university websites.

— The basic principles, framework conditions, and specific measures aimed at creating a modern digital infrastructure of scientific and technological information in the Russian Federation are discussed along with the organizational, political, economic, and legal aspects of setting up a digital infrastructure of scientific and technological information.

Computer architecture is an essential topic in undergraduate Computer Science (CS) curricula. Teaching computer architecture courses to CS students can be challenging, as the concepts are on a high abstraction level and not easy to grasp for students. Learning of computer architecture abstracts is strongly reinforced by hands-on assignment experience. This paper presents results from a survey of assignments from 40 undergraduate computer architecture courses, which are offered in 40 CS departments. These surveyed courses are selected from universities listed among the 120 top North America universities by the Webometrics Ranking of World Universities 2015. The information used for this survey is based solely on material publicly accessible on the websites of courses.

Purpose – This study aims to map the information landscape as it unfolds to users when they search for health topics on general search engines. Website sponsorship, platform type and linking patterns were analysed in order to advance the understanding of the provision of health information online. Design/methodology/approach – The landscape was sampled by ten very different search queries and crawled with VOSON software. Drawing on Roger's framework of information politics on the web, the landscape is described on two levels. The front-end is examined qualitatively by assessing website sponsorship and platform type. On the back-end, linking patterns are analysed using hyperlink network analysis. Findings – A vast majority of the websites have commercial and organisational sponsorship. The analysis of the platform type shows that health information is provided mainly on static homepages, informational portals and general news sites. A comparison of ten different health domains revealed substantial differences in their landscapes, related to domain-specific characteristics. Research limitations/implications – The size and properties of the web crawl were shaped by using third party software, and the generalisability of the results is limited by the selected search queries. Further research exploring how specific characteristics of different health domains shape provision of information online is suggested. Practical implications – The demonstrated method can be used by organisations to discern the characteristics of the online information landscape in which they operate and to inform their business strategies. Originality/value – The study examines health information landscapes on a large scale and makes an original contribution by comparing them across ten different health domains.

This article presents a methodology for calculating the aggregate global university ranking (Aggregated Global University Ranking (AGUR), which consists of an automated presentation of the comparable lists of names for different universities from particular global university rankings (using Machine Learning and Mining Data algorithms) and a simple procedure of aggregating particular global university rankings (summing up the university ranking positions from different particular rankings and their subsequent ranking). The second procedure makes it possible to bring lists of universities from particular rankings, which are nonidentical by length, to one size. This article includes a sample AGUR for six particular global university rankings as of 2013, as well as cross-correlation matrices and intersection matrices for AGUR for 2011-2013, all created by means of using the Python-based software.

According to Thomas and Thomas, over the last three decades rapid growth and development has occurred in the area of information and communication technologies. Particularly in the last decade, the growth in prominence of social media and Web 2.0 technologies has had a dramatic impact globally on how people communicate. Social media platforms such as Facebook, Twitter, Linkedin, Google+ and Renren have the potential to become important disruptive technologies for building cutting-edge models of management education. It should be noted that the 21st century client is technologically affluent and expects more from the academic units. New students entering Universities today can be said to not only require information but also a memorable experience. Lenhart in Canuel and Crichton contend that by the age of 17, 84% of American children have had contact with computers and smart phones. In South Africa, Uganda and Tanzania, mobile and broadband penetration continues to rise faster than many other sectors on the economy.

Webometrics, the quantitative study of Web phenomena, is a field encompassing contributions from information science, computer science, and statistical physics. Its methodology draws especially from bibliometrics. This special issue presents contributions that both push forward the field and illustrate a wide range of webometric approaches.