Analysis of (dis)agreement among aggregators in Mendeley readership counts.

<p>Analysis of (dis)agreement among aggregators in Mendeley readership counts.</p

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

<div><p>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.</p></div

Coverage (% of DOIs with at least one metric) of PloS ONE DOIs across altmetric aggregators and aggregators and per data sources.

<p>Coverage (% of DOIs with at least one metric) of PloS ONE DOIs across altmetric aggregators and aggregators and per data sources.</p

Examples of different readership counts across different altmetric aggregators: Plum Analytics, Altmetric.com, and Lagotto vs. Mendeley (accessed on 15 December 2017).

<p>Examples of different readership counts across different altmetric aggregators: Plum Analytics, Altmetric.com, and Lagotto vs. Mendeley (accessed on 15 December 2017).</p

Proportion of top 1% most cited papers, as a function of their number of papers published, for the cohort of researchers who have published their first paper between 2009 and 2013, by domain.

<p>Only classes of numbers of papers with 30 researchers or more are shown. Power trendlines and R2 are used for natural sciences and social and behavioral sciences, while 2nd order polynomials are used for medical and life sciences, and law, arts and humanities.</p

Analysis of (dis)agreement among aggregators in Twitter counts (re)tweets, and distinct tweeters.

<p>Analysis of (dis)agreement among aggregators in Twitter counts (re)tweets, and distinct tweeters.</p

Pearson correlation analysis across different aggregators and their Wikipedia counts.

<p>Pearson correlation analysis across different aggregators and their Wikipedia counts.</p

Examples of different readership counts across different altmetric aggregators: Plum Analytics vs. Mendeley (accessed on 15 December 2017).

<p>Examples of different readership counts across different altmetric aggregators: Plum Analytics vs. Mendeley (accessed on 15 December 2017).</p

Examples of different tweets (tweeters) across different altmetric aggregators: Plum Analytics, Altmetric.com, and Lagotto are presented orderly (accessed on 29 November 2017).

<p>Examples of different tweets (tweeters) across different altmetric aggregators: Plum Analytics, Altmetric.com, and Lagotto are presented orderly (accessed on 29 November 2017).</p

Pearson correlation analysis across different aggregators and their Facebook counts.

<p>Pearson correlation analysis across different aggregators and their Facebook counts.</p