Scale to estimate the aspect-oriented sentiment polarity under anaphors influence (SPAI)
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Post-publication record
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Abstract
Purpose The purpose of this paper is to handle the anaphors through anaphora resolution in aspect-oriented sentiment analysis. Sentiment analysis is one of the predictive analytics of social media. In particular, the social media platform Twitter is an open platform to post the opinion by subscribers on contextual issues, events, products, individuals and organizations. Design/methodology/approach The sentiment polarity assessment is not deterministic to conclude the opinion of the target audience unless the polarity is assessed under diversified aspects. Hence, the aspect-oriented sentiment polarity assessment is a crucial objective of the opinion assessment over social media. However, the aspect-oriented sentiment polarity assessment often influences by the curse of anaphora resolution. Findings Focusing on these limitations, a scale to estimate the aspects oriented sentiment polarity under anaphors influence has been portrayed in this article. To assess the aspect-based sentiment polarity of the tweets, the anaphors of the tweets have been considered to assess the weightage of the tweets toward the sentiment polarity. Originality/value The experimental study presents the performance of the proposed model by comparing it with the contemporary models, which are estimating the sentiment polarity tweets under anaphors impact.
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The record
- Venue
- International Journal of Intelligent Unmanned Systems
- Topic
- Sentiment Analysis and Opinion Mining
- Field
- Computer Science
- Canadian institutions
- Tellabs (Canada)
- Funders
- —
- Keywords
- Sentiment analysisPolarity (international relations)Social mediaComputer scienceNatural language processingScale (ratio)OriginalityAnaphora (linguistics)Resolution (logic)Artificial intelligenceData sciencePsychologyWorld Wide WebSocial psychologyChemistry
- Has abstract in OpenAlex
- yes