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Sentiment Analysis of Algorithms using VIKOR Method

Sentiment Analysis of Algorithms using VIKOR Method

Abstract

Sentiment analysis in VIKOR Method. Sentiment analysis is a product or a positive about the topic, Negative or neutral opinion of the text Determines whether a part is expressive It is an automated process. Sentiment By using analysis, Survey responses, reviews, support to encode customer data like Companies put in endless hours No need to spend. In the predictive process, the invisible a feature to convert text into feature vectors Extraction is used, they are. From this analysis the VIKOR technique is the most accurate determines a worst-case-good solution, however, is variation these Distance is not taken into account. VIKOR the approach is Multi-Criteria Selection (MCDM) or Multicriteria selection is an evaluation technique.Alternative: Accuracy (%),Precision (%),Recall (%), Score (%).Assessment Option: KNN, Decision Tree, SVM, Logistic Regression, Naïve Bays, Random Forest, Google,Microsoft,Twitter. It is solved by using the VIKOR method. It is the data set of this paper. The result it is seen that Naïve Bayesis got the first rank where as is the Logistic Regressionis Very low rank. In this paper Naïve Bayesis got the first rank whereas is the Logistic Regressionis having the lowest rank.

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    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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