General discussion of data quality challenges in social media metrics: Extensive comparison of four major altmetric data aggregators

PLoS One. 2018 May 17;13(5):e0197326. doi: 10.1371/journal.pone.0197326. eCollection 2018.

Abstract

The data collection and reporting approaches of four major altmetric data aggregators are studied. The main aim of this study is to understand how differences in social media tracking and data collection methodologies can have effects on the analytical use of altmetric data. For this purpose, discrepancies in the metrics across aggregators have been studied in order to understand how the methodological choices adopted by these aggregators can explain the discrepancies found. Our results show that different forms of accessing the data from diverse social media platforms, together with different approaches of collecting, processing, summarizing, and updating social media metrics cause substantial differences in the data and metrics offered by these aggregators. These results highlight the importance that methodological choices in the tracking, collecting, and reporting of altmetric data can have in the analytical value of the data. Some recommendations for altmetric users and data aggregators are proposed and discussed.

Publication types

  • Comparative Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Data Collection / methods*
  • Humans
  • Social Media*

Associated data

  • figshare/10.6084/m9.figshare.6061262.v1

Grants and funding

The idea of this study received the first altmetrics project funding award at the 1:AM altmetrics conference, September 2014, London (UK). The authors are grateful for the fundings awarded by Thomson Reuters/Altmetric.com. We also acknowledge funding from the South African DST-NRF Centre of Excellence in Scientometrics and Science, Technology and Innovation Policy (SciSTIP).