# Predicting Patent Citations to measure Economic Impact of Scholarly Research

arXiv: https://arxiv.org/abs/1906.08244 · HTML: https://mlsanity.com/paper/1906.08244/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 7 Jun 2019.

## Built on by (most cited first, 3 of 3)

- [YouTube and Science: Models for Research Impact](https://mlsanity.com/paper/2209.02380/) (2022)
- [Quantifying the Online Long-Term Interest in Research](https://mlsanity.com/paper/2209.06212/) (2022)
- [Public Reaction to Scientific Research via Twitter Sentiment Prediction](https://mlsanity.com/paper/2209.07333/) (2022)

## Abstract (arXiv)

A crucial goal of funding research and development has always been to advance economic development. On this basis, a consider-able body of research undertaken with the purpose of determining what exactly constitutes economic impact and how to accurately measure that impact has been published. Numerous indicators have been used to measure economic impact, although no single indicator has been widely adapted. Based on patent data collected from Altmetric we predict patent citations through various social media features using several classification models. Patents citing a research paper implies the potential it has for direct application inits field. These predictions can be utilized by researchers in deter-mining the practical applications for their work when applying for patents.