Aspect-based opinion ranking framework for product reviews using a Spearman's rank correlation coefficient method

J, Ashok Kumar; Abirami, S.

doi:10.1016/j.ins.2018.05.003

Cited by 47 publications

(9 citation statements)

References 18 publications

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“…A straightforward and trustworthy technique for analyzing data is gray relational analysis . According to Sedgwick, the Pearson correlation coefficient is mostly utilized to analyze the linear relationships between data, whereas Kendall and Spearman correlation coefficients are employed to determine the correlation between data by resolving the rank of the data matrix. The positive and negative Pearson, Kendall, and Spearman correlation coefficients represent positive and negative correlation, respectively, and the size represents the degree of correlation.…”

Section: Methodsmentioning

confidence: 99%

Integration of Domain Knowledge and Data-Driven Modeling Evaluation Process for Predicting Minimum Miscible Pressure of CO₂–Oil Systems in CCUS

Zhang,

Xu,

Wang

et al. 2023

Energy Fuels

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Section: Methodsmentioning

confidence: 99%

Integration of Domain Knowledge and Data-Driven Modeling Evaluation Process for Predicting Minimum Miscible Pressure of CO₂–Oil Systems in CCUS

Zhang,

Xu,

Wang

et al. 2023

Energy Fuels

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“…Besides, the authors proved that experimental results have a strong correlation with actual sales ranking by applying the Spearman coefficient. In the same year, Kumar J and Abirami [74] proposed a framework to solve the problem of ranking alternative products (through reviews) based on aspects of products. They used the OpinRank review dataset in English, which contains 42,230 reviews to identify the aspects and opinion words, by applying a Harel-Koren fast multiscale layout.…”

Section: Ranking Products Based On Online Reviewsmentioning

confidence: 99%

“…The most important contributions in each stage can be summarized. The contributions of this paper compared to the existing literature such as [1] [4], [5], [7], [73], [74], [81], [87] [90]- [98] can be divided into two parts, the sentiment analysis part and ranking part.…”

Section: Comparative Analysismentioning

confidence: 99%

Sentiment Analysis Technique and Neutrosophic Set Theory for Mining and Ranking Big Data From Online Reviews

2021

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Recently, a huge amount of online consumer reviews (OCRs) is being generated through social media, web contents, and microblogs. This scale of big data cannot be handled by traditional methods. Sentiment analysis (SA) or opinion mining is emerging as a powerful and efficient tool in big data analytics and improving decision making. This research paper introduces a novel method that integrates neutrosophic set (NS) theory into the SA technique and multi-attribute decision making (MADM) to rank the different products based on numerous online reviews. The method consists of two parts: Determining sentiment scores of the online reviews based on the SA technique and ranking alternative products via NS theory. In the first part, the online reviews of the alternative products concerning multiple features are crawled and pre-processed. A neutral lexicon consists of 228 neutral words and phrases is compiled and the Valence Aware Dictionary and sEntiment Reasoner (VADER) for sentiment reasoning is adapted to handle the neutral data. The compiled neutral lexicon, as well as the adapted VADER, are utilized to build a novel adaptation called Neutro-VADER. The Neutro-VADER assigns positive, neutral, and negative sentiment scores to each review concerning the product feature. In this stage, the novel idea is to point out the positive, neutral, and negative sentiment scores as the truth, indeterminacy, and falsity memberships degrees of the neutrosophic number. The overall performance of each alternative concerning each feature based on a neutrosophic number is measured. In the second part, the ranking of alternatives is being evaluated through the simplified neutrosophic number weighted averaging (SNNWA) operator and cosine similarity measure methods. A case study with real datasets (Twitter datasets) is provided to illustrate the application of the proposed method. The results show good performance in handling the neutral data on the SA stage as well as the ranking stage. In the SA stage, findings show that the Neutro-VADER in the proposed method can deal successfully with all types of uncertainties including indeterminacy comparable with the traditional VADER in the other methods. In the ranking stage, the results show a great similarity and consistency while using other ranking methods such as PROMETHEE II, TOPSIS, and TODIM methods.

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“…The analysis was performed with the use of STATISTICA software package. On that basis it was possible to determine the influence of independent variables, i.e., the amount of biomass and boiler output on dependent variables, i.e., changes in the concentration of individual pollutants and boiler efficiency [50][51][52][53]. The diagram in Figure 4 shows that with the increase in boiler output and the share of biomass, the amount of carbon dioxide in flue gases increased.…”

Section: Figure 2 and Tablementioning

confidence: 99%

Co-Combustion of Biomass with Coal in Grate Water Boilers at Low Load Boiler Operation

Nowak

Rabczak

2021

Energies

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Environmental protection, and in particular air protection against pollution, is an extremely important element of the global policy of many countries. The problem of air pollution is particularly important in Poland, where the heating market is one of the largest in Europe and is based in 74% on the use of fossil fuels, in particular hard coal. One of the technological solutions for the implementation of cleaner fuels is the co-combustion of coal and biomass. This process enables the reduction of harmful pollutants such as CO2, SO2, and can be implemented in existing boilers. Heating boilers achieve the highest design efficiency during optimal load at the level of 85–95% of nominal power. Under such conditions, heat production is most efficient. During operation, boilers are often started, extinguished or run below rated output, resulting in increased emissions. This publication presents the results of measurements of efficiency and concentrations of pollutants in the WR water boiler during operation below the technical minimum. Hard coal was cofired in the boiler with biomass of wood origin. It was noted that the amount of biomass had a significant impact on the boiler efficiency and pollutant emission. Based on the research, it was also noted that it was possible to make a qualitative prediction of these parameters. The obtained results are an introduction to a deeper analysis and further research on the correlation between the amount of biomass and boiler power and the efficiency and concentration of pollutants.

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Aspect-based opinion ranking framework for product reviews using a Spearman's rank correlation coefficient method

Cited by 47 publications

References 18 publications

Integration of Domain Knowledge and Data-Driven Modeling Evaluation Process for Predicting Minimum Miscible Pressure of CO₂–Oil Systems in CCUS

Integration of Domain Knowledge and Data-Driven Modeling Evaluation Process for Predicting Minimum Miscible Pressure of CO₂–Oil Systems in CCUS

Sentiment Analysis Technique and Neutrosophic Set Theory for Mining and Ranking Big Data From Online Reviews

Co-Combustion of Biomass with Coal in Grate Water Boilers at Low Load Boiler Operation

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Aspect-based opinion ranking framework for product reviews using a Spearman's rank correlation coefficient method

Cited by 47 publications

References 18 publications

Integration of Domain Knowledge and Data-Driven Modeling Evaluation Process for Predicting Minimum Miscible Pressure of CO2–Oil Systems in CCUS

Integration of Domain Knowledge and Data-Driven Modeling Evaluation Process for Predicting Minimum Miscible Pressure of CO2–Oil Systems in CCUS

Sentiment Analysis Technique and Neutrosophic Set Theory for Mining and Ranking Big Data From Online Reviews

Co-Combustion of Biomass with Coal in Grate Water Boilers at Low Load Boiler Operation

Contact Info

Product

Resources

About

Integration of Domain Knowledge and Data-Driven Modeling Evaluation Process for Predicting Minimum Miscible Pressure of CO₂–Oil Systems in CCUS

Integration of Domain Knowledge and Data-Driven Modeling Evaluation Process for Predicting Minimum Miscible Pressure of CO₂–Oil Systems in CCUS