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

Adrián A. Díaz-Faes, Nicolás Robinson-García, Timothy D. Bowman, Rodrigo Costas

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

1 Citation (Scopus)

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.

Original languageEnglish
Title of host publication17th International Conference on Scientometrics and Informetrics, ISSI 2019 - Proceedings
EditorsGiuseppe Catalano, Cinzia Daraio, Martina Gregori, Henk F. Moed, Giancarlo Ruocco
PublisherInternational Society for Scientometrics and Informetrics
Pages2070-2075
Number of pages6
Volume2
ISBN (Electronic)9788833811185
Publication statusPublished - 2019
Event17th International Conference on Scientometrics and Informetrics, ISSI 2019 - Rome, Italy
Duration: 2 Sept 20195 Sept 2019

Conference

Conference17th International Conference on Scientometrics and Informetrics, ISSI 2019
Country/TerritoryItaly
CityRome
Period2/09/195/09/19

Fingerprint

Dive into the research topics of 'Towards a multidimensional classification of social media users around science on Twitter'. Together they form a unique fingerprint.

Cite this