A search of almost any topic on Google Scholar promises to return tens of thousands of hits in less than a second. The first step in any research endeavour is to wade through the titanic amounts of articles available to become acquainted with the existing knowledge. For many people it’s one of the most dreadful and tedious parts of the scientific process.
But what if we could streamline/facilitate this step by automatizing parts of it? Automated content analysis (ACA) gives us the opportunity to do just that. ACA – a text-mining method that uses text-parsing and machine learning – is able to classify vast amounts of text into categories of named concepts. It can then quantify the frequency of those concepts and the relationships among them. Continue reading →
This post is an outcome of the ‘Maximising the Exposure of Your Research’ Workshop at the BES 2015 Annual Meeting in Edinburgh (UK). If you’re interested in joining us for our 2016 Annual Meeting in Liverpool (UK), you can find some more information and pre-register HERE.
In recent years there has been a significant increase in the number of academic articles published. At the same time, readers are changing how they find content, tending towards a point of entry at article level as opposed to journal level. These two factors mean that it is increasingly necessary for authors to make their articles easy for relevant readers to find. Search Engine Optimisation (SEO) is one of the best ways to do this.
While writing your paper, there are a few things that you can do to optimise it for search engines, such as Google Scholar. The tips below focus on three areas that are prioritised by search engines when looking for content. Following these tips will help you to maximise the exposure of your research. Continue reading →