Towards a multidimensional classification of social media users around science on Twitter

Abstract

With the advent of altmetrics, digital traces that go beyond the scientific impact can be tracked. Twitter stands as the most appealing platform for their inspection since it gathers academic and non-academic users that discuss a wide-ranging number of topics. This research aims at developing and proposing a fine-grained classification of social media users based on mapping techniques and clustering methods and compare them with other tentative classifications proposed elsewhere. To do so, online activity of over 1.3 million Twitter users is examined, considering both their overall activity on Twitter as well as their interaction with scientific publications.