An Overview of Altmetrics Research: A Typology Approach

Altmetrics, novel metrics based on social media, have received much attention from scholars in recent years. As an emerging research area in information science, it is essential to understand the overview of altmetrics research. We extracted 731 altmetrics-related articles from the Scopus databases and adopted a text mining method (i.e., topic modeling) to develop a typology of altmetrics research. Six major themes were identified in our analysis, including altmetrics research in general, bibliometric and altmetrics, measuring research impact, metrics application, social media use, and performance evaluation. We interpreted the meaning of the six themes and their associations with altmetrics research. This paper is a first step in mapping the landscape of altmetrics research through uncovering the core topics discussed by scholars. Limitations and future work are also discussed.

[1]  Shenmeng Xu,et al.  Is there Lingua Franca in informal scientific communication? Evidence from language distribution of scientific tweets , 2018, J. Informetrics.

[2]  Katrin Weller.  Social Media and Altmetrics: An Overview of Current Alternative Approaches to Measuring Scholarly Impact , 2015 .

[3]  Michalis Sfakakis,et al.  Discovering the structure and impact of the digital library evaluation domain , 2019, International Journal on Digital Libraries.

[4]  Yin Leng Theng,et al.  Altmetrics: an analysis of the state-of-the-art in measuring research impact on social media , 2016, Scientometrics.

[5]  Ian Rowlands,et al.  Social media use in the research workflow , 2011, Inf. Serv. Use.

[6]  Cassidy R. Sugimoto,et al.  Do Altmetrics Work? Twitter and Ten Other Social Web Services , 2013, PloS one.

[7]  Yin-Leng Theng,et al.  Social media presence of scholarly journals , 2018, J. Assoc. Inf. Sci. Technol..

[8]  Jonathan Furner,et al.  Scholarly communication and bibliometrics , 2005, Annu. Rev. Inf. Sci. Technol..

[9]  Mojisola Erdt,et al.  How Do Scholars Evaluate and Promote Research Outputs? An NTU Case Study , 2018 .

[10]  D. Harley.  Scholarly Communication: Cultural Contexts, Evolving Models , 2013, Science.

[11]  Alton Yeow-Kuan Chua,et al.  Reviewing the landscape of research on the threats to the quality of user‐generated content , 2016, ASIST.

[12]  David Newman,et al.  Are learned topics more useful than subject headings , 2011, JCDL '11.

[13]  Joe Bungo,et al.  Embedded Systems Programming in the Cloud: A Novel Approach for Academia , 2011, IEEE Potentials.

[14]  Rodrigo Costas,et al.  How well developed are altmetrics? A cross-disciplinary analysis of the presence of ‘alternative metrics’ in scientific publications , 2014, Scientometrics.

[15]  Gunther Eysenbach,et al.  Can Tweets Predict Citations? Metrics of Social Impact Based on Twitter and Correlation with Traditional Metrics of Scientific Impact , 2011, Journal of medical Internet research.

[16]  Hiroshi Nakagawa,et al.  Automatic Term Extraction Based on Perplexity of Compound Words , 2005, IJCNLP.

[17]  A. Chua,et al.  The shift towards multi-disciplinarity in information science , 2008 .

[18]  Rob Atenstaedt,et al.  Word cloud analysis of the BJGP. , 2012, The British journal of general practice : the journal of the Royal College of General Practitioners.

[19]  Michael I. Jordan,et al.  Latent Dirichlet Allocation , 2001, J. Mach. Learn. Res..

[20]  Ian Rowlands,et al.  Social media use in the research workflow , 2011 .

[21]  Sei-Ching Joanna Sin,et al.  Investigating familiarity and usage of traditional metrics and altmetrics , 2019, J. Assoc. Inf. Sci. Technol..