This paper presents a review of altmetrics or alternative metrics. This concept is defined as the creation and study of new indicators for analysing scientific and academic research activity based onWeb 2.0. The underlying premise is that variables such as mentions in blogs, numberof tweets or saves ofan articleby researchersin reference management systems, may be a valid measure of the use and impactof scientific publications. In this respect,these measuresare becoming particularly relevant, being at the centre of debate within the bibliometric community. Firstly,an explanation is given of the main platforms and indicators for this type of measurement. Subsequently,a study is undertaken of a selection of papers from the field of communication, comparing the number of citations received withtheir 2.0 indicators.The results show that the most cited articles within recent years also have significantly higher altmetric indicators. Next follows a review of the principal empirical studies undertaken, centering on the correlations between bibliometric and alternative indicators. To conclude, the main limitations of altmetrics are highlighted,alongside a reflective consideration of the role altmetrics may play in capturing the impactof research in Web 2.0 platforms.
The aim of this paper is to present the Information Literacy Instruction Assessment Cycle (ILIAC), to describe the seven stages of the ILIAC, and to offer an extended example that demonstrates how the ILIAC increases librarian instructional abilities and improves student information literacy skills.
a tool by the Electronic Frontier Foundation that tests your browser "fingerprint" to see how unique it is based on the information it will share with sites it visits.
Free online biodiversity encyclopedia, with hundreds of thousands of new images and specimen data as to build a web page for each of the 1.9 million recognized species.
Short introduction to Vector Space Model (VSM) In information retrieval or text mining, the term frequency - inverse document frequency also called tf-idf, is
G. Feng, T. Liu, Y. Wang, Y. Bao, Z. Ma, X. Zhang, and W. Ma. Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval - SIGIR \textquotesingle06, ACM Press, (2006)