# Quantifying the Online Long-Term Interest in Research

arXiv: https://arxiv.org/abs/2209.06212 · HTML: https://mlsanity.com/paper/2209.06212/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 16 of its 86 references that are in the map.
- First posted on arXiv 13 Sep 2022.

## Builds on (most cited first, 16 of 16)

- [Quantifying Long-Term Scientific Impact](https://mlsanity.com/paper/1306.3293/) (2013)
- [Predicting the long-term citation impact of recent publications](https://mlsanity.com/paper/1503.09156/) (2015)
- [Do altmetrics point to the broader impact of research? An overview of benefits and disadvantages of altmetrics](https://mlsanity.com/paper/1406.7091/) (2014)
- [Measuring the Diversity of Facebook Reactions to Research](https://mlsanity.com/paper/2001.01029/) (2020)
- [Could scientists use Altmetric.com scores to predict longer term citation counts?](https://mlsanity.com/paper/1801.10311/) (2018)
- [Predicting long-term publication impact through a combination of early citations and journal impact factor](https://mlsanity.com/paper/1909.08907/) (2019)
- [Early Indicators of Scientific Impact: Predicting Citations with Altmetrics](https://mlsanity.com/paper/2012.13599/) (2020)
- [Shared Feelings: Understanding Facebook Reactions to Scholarly Articles](https://mlsanity.com/paper/1905.10975/) (2019)
- [Scholarly use of social media and altmetrics: a review of the literature](https://mlsanity.com/paper/1608.08112/) (2016)
- [Back to the past: on the shoulders of an academic search engine giant](https://mlsanity.com/paper/1603.09111/) (2016)
- [Understanding the Impact of Early Citers on Long-Term Scientific Impact](https://mlsanity.com/paper/1705.03178/) (2017)
- [Predicting Patent Citations to measure Economic Impact of Scholarly Research](https://mlsanity.com/paper/1906.08244/) (2019)
- [Genesis of Altmetrics or Article-level Metrics for Measuring Efficacy of Scholarly Communications: Current Perspectives](https://mlsanity.com/paper/1408.0090/) (2014)
- [Influence of Reviewer Interaction Network on Long-term Citations: A Case Study of the Scientific Peer-Review System of the Journal of High Energy Physics](https://mlsanity.com/paper/1705.01089/) (2017)
- [Social media metrics for new research evaluation](https://mlsanity.com/paper/1806.10541/) (2018)
- [Knowledge spillovers: does the geographic proximity effect decay over time? A discipline-level analysis, accounting for cognitive proximity, with and without self-citations](https://mlsanity.com/paper/2103.13819/) (2021)

## Built on by (most cited first, 1 of 1)

- [Public interest in science or bots? Selective amplification of scientific articles on Twitter](https://mlsanity.com/paper/2410.01842/) (2024)

## Abstract (arXiv)

Research articles are being shared in increasing numbers on multiple online platforms. Although the scholarly impact of these articles has been widely studied, the online interest determined by how long the research articles are shared online remains unclear. Being cognizant of how long a research article is mentioned online could be valuable information to the researchers. In this paper, we analyzed multiple social media platforms on which users share and/or discuss scholarly articles. We built three clusters for papers, based on the number of yearly online mentions having publication dates ranging from the year 1920 to 2016. Using the online social media metrics for each of these three clusters, we built machine learning models to predict the long-term online interest in research articles. We addressed the prediction task with two different approaches: regression and classification. For the regression approach, the Multi-Layer Perceptron model performed best, and for the classification approach, the tree-based models performed better than other models. We found that old articles are most evident in the contexts of economics and industry (i.e., patents). In contrast, recently published articles are most evident in research platforms (i.e., Mendeley) followed by social media platforms (i.e., Twitter).