Citation Sentiment Changes Analysis
Haixia Liu

TL;DR
This paper introduces metrics and an EDR-based method to analyze how citation sentiments evolve over time, providing a new way to assess a publication's impact through citation sentiment sequences.
Contribution
It presents a novel approach using Eddy Dissipation Rate to analyze global citation sentiment sequences and detect pattern differences over time.
Findings
EDR-based method can identify citation sentiment pattern changes
Preliminary results suggest potential for impact analysis
Method shows promise for time series citation sentiment analysis
Abstract
Metrics for measuring the citation sentiment changes were introduced. Citation sentiment changes can be observed from global citation sentiment sequences (GCSSs). With respect to a cited paper, the citation sentiment sequences were analysed across a collection of citing papers ordered by the published time. For analysing GCSSs, Eddy Dissipation Rate (EDR) was adopted, with the hypothesis that the GCSSs pattern differences can be spotted by EDR based method. Preliminary evidence showed that EDR based method holds the potential for analysing a publication's impact in a time series fashion.
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Taxonomy
TopicsAdvanced Text Analysis Techniques · Complex Network Analysis Techniques · Sentiment Analysis and Opinion Mining
