e-space
Manchester Metropolitan University's Research Repository

Predicting literature’s early impact with sentiment analysis in Twitter

Hassan, Saeed-Ul and Aljohani, Naif R and Idrees, Nimra and Sarwar, Raheem and Nawaz, Raheel and Martínez-Cámara, Eugenio and Ventura, Sebastián and Herrera, Francisco (2019) Predicting literature’s early impact with sentiment analysis in Twitter. Knowledge-Based Systems. ISSN 0950-7051

[img]
Restricted to Repository staff only until 14 December 2020.
Available under License Creative Commons Attribution Non-commercial No Derivatives.

Download (1MB)

Abstract

Traditional bibliometric techniques gauge the impact of research through quantitative indices based on the citations data. However, due to the lag time involved in the citation-based indices, it may take years to comprehend the full impact of an article. This paper seeks to measure the early impact of research articles through the sentiments expressed in tweets about them. We claim that cited articles in either positive or neutral tweets have a more significant impact than those not cited at all or cited in negative tweets. We used the SentiStrength tool and improved it by incorporating new opinion-bearing words into its sentiment lexicon pertaining to scientific domains. Then, we classified the sentiment of 6,482,260 tweets linked to 1,083,535 publications covered by Altmetric.com. Using positive and negative tweets as an independent variable, and the citation count as the dependent variable, linear regression analysis showed a weak positive prediction of high citation counts across 16 broad disciplines in Scopus. Introducing an additional indicator to the regression model, i.e. ‘number of unique Twitter users’, improved the adjusted R-squared value of regression analysis in several disciplines. Overall, an encouraging positive correlation between tweet sentiments and citation counts showed that Twitter-based opinion may be exploited as a complementary predictor of literature’s early impact.

Impact and Reach

Statistics

Downloads
Activity Overview
1Download
52Hits

Additional statistics for this dataset are available via IRStats2.

Altmetric

Actions (login required)

Edit Item Edit Item