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

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

Zohreh Zahedi  1 , Rodrigo Costas  1   2
Affiliations
Comparative Study

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

Zohreh Zahedi et al. PLoS One. .

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.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Examples of different readership counts across different altmetric aggregators: Plum Analytics vs. Mendeley (accessed on 15 December 2017).
Fig 2
Fig 2. Examples of different readership counts across different altmetric aggregators: Plum Analytics, Altmetric.com, and Lagotto vs. Mendeley (accessed on 15 December 2017).
Fig 3
Fig 3. Examples of different Mendeley readership counts across different altmetric aggregators: Mendeley, Plum Analytics, Altmetric.com, and Lagotto are presented orderly (accessed on 29 November 2017).
Fig 4
Fig 4. Examples of different Facebook counts across different altmetric aggregators: Plum Analytics, Lagotto, and Altmetirc.com are presented orderly (accessed on 29 November 2017).
Fig 5
Fig 5. Examples of different tweets (tweeters) across different altmetric aggregators: Plum Analytics, Altmetric.com, and Lagotto are presented orderly (accessed on 29 November 2017).
Fig 6
Fig 6. Examples of Wikipedia counts for an object reported by Lagotto (accessed on 29 November 2017).
Fig 7
Fig 7. Examples of different Wikipedia mentions across different altmetric aggregators: Lagotto, Altmetric.com, and Plum Analytics are presented orderly (accessed on 29 November 2017).
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References

    1. Wouters P., Zahedi Z., & Costas R. (2018). Social media metrics for new scientific evaluations In Glänzel W., Moed H. F., Schmoch U., & Thelwall M. (Eds.), Handbook of Quantitative Science and Technology Research. Springer.
    1. Costas R. (2017). Towards the social media studies of science: social media metrics, present and future. Bibliotecas Anales de Investigación, 13(1), 1–5.
    1. Haustein S. (2016). Grand challenges in altmetrics: heterogeneity, data quality and dependencies. Scientometrics, 108(1), 413–423.
    1. Halevi G., Moed H., & Bar-Ilan J. (2017). Suitability of Google Scholar as a source of scientific information and as a source of data for scientific evaluation? Review of the Literature. Journal of Informetrics, 11(3), 823–834. doi: 10.1016/j.joi.2017.06.005 - DOI
    1. Moed H. F., Bar-Ilan J., & Halevi G. (2016). A new methodology for comparing Google Scholar and Scopus. Journal of Informetrics, 10(2), 533–551. doi: 10.1016/j.joi.2016.04.017 - DOI

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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).

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