# Could scientists use Altmetric.com scores to predict longer term citation counts?

arXiv: https://arxiv.org/abs/1801.10311 · HTML: https://mlsanity.com/paper/1801.10311/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 31 Jan 2018.

## Built on by (most cited first, 6 of 6)

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- [Artificial intelligence technologies to support research assessment: A review](https://mlsanity.com/paper/2212.06574/) (2022)
- [A Graph Convolutional Neural Network based Framework for Estimating Future Citations Count of Research Articles](https://mlsanity.com/paper/2104.04939/) (2021)
- [Predicting the Citation Count and CiteScore of Journals One Year in Advance](https://mlsanity.com/paper/2210.12908/) (2022)

## Abstract (arXiv)

Altmetrics from Altmetric.com are widely used by publishers and researchers to give earlier evidence of attention than citation counts. This article assesses whether Altmetric.com scores are reliable early indicators of likely future impact and whether they may also reflect non-scholarly impacts. A preliminary factor analysis suggests that the main altmetric indicator of scholarly impact is Mendeley reader counts, with weaker news, informational and social network discussion/promotion dimensions in some fields. Based on a regression analysis of Altmetric.com data from November 2015 and Scopus citation counts from October 2017 for articles in 30 narrow fields, only Mendeley reader counts are consistent predictors of future citation impact. Most other Altmetric.com scores can help predict future impact in some fields. Overall, the results confirm that early Altmetric.com scores can predict later citation counts, although less well than journal impact factors, and the optimal strategy is to consider both Altmetric.com scores and journal impact factors. Altmetric.com scores can also reflect dimensions of non-scholarly impact in some fields.