Matches in SemOpenAlex for { <https://semopenalex.org/work/W4385187369> ?p ?o ?g. }
Showing items 1 to 81 of
81
with 100 items per page.
- W4385187369 abstract "Customer feedback play an important role in assisting the organization. Sentiment analysis of the customer feedback takes the business to next level of profit making. Based on the sentiment or the opinion of the customer organization can identify the needs of the customer. Sentiment analysis is applicable not only for the customer feedback analysis, it can also be used employee review system. To create the sentiment analysis model supervised machine learning algorithm can be used extensively. Supervised learning algorithm is used for training the model for classification and regression problem. In this article various learning algorithm like linear regression, KNN, SVM, Random Forest, Bagging and Gradient Boosting are considered for developing and testing the model. The dataset was divided into training and test dataset. The model was developed using the training dataset and tested on the test dataset. The data was collected from 884 employees working in different organizations. The reliability control has shown that 1.1 % of respondents were unreliable, as some questions were left unattended. The final data of 802 employees was taken for the study. The different lexical resources like Afinn, VADER and sentiment from textblob were considered for determining the sentiment related to all the three dimensions of positive leadership those are strength, perspective and recognition. The result shows that random forest supervised machine learning algorithm gives the highest accuracy of 0.711 whereas the KNN algorithm gives the accuracy of 0.515." @default.
- W4385187369 created "2023-07-25" @default.
- W4385187369 creator A5032370728 @default.
- W4385187369 creator A5059418768 @default.
- W4385187369 creator A5091397373 @default.
- W4385187369 creator A5091947030 @default.
- W4385187369 date "2023-02-22" @default.
- W4385187369 modified "2023-09-26" @default.
- W4385187369 title "Sentiment Analysis Perspective using Supervised Machine Learning Method" @default.
- W4385187369 cites W2546699506 @default.
- W4385187369 cites W2585826245 @default.
- W4385187369 cites W2593754960 @default.
- W4385187369 cites W2743243853 @default.
- W4385187369 cites W2756042874 @default.
- W4385187369 cites W2761561877 @default.
- W4385187369 cites W2787215646 @default.
- W4385187369 cites W2897209446 @default.
- W4385187369 cites W2903394456 @default.
- W4385187369 cites W2966409253 @default.
- W4385187369 cites W2966861509 @default.
- W4385187369 cites W2984952311 @default.
- W4385187369 cites W2998433004 @default.
- W4385187369 cites W3102444842 @default.
- W4385187369 cites W327938509 @default.
- W4385187369 doi "https://doi.org/10.1109/icecct56650.2023.10179807" @default.
- W4385187369 hasPublicationYear "2023" @default.
- W4385187369 type Work @default.
- W4385187369 citedByCount "0" @default.
- W4385187369 crossrefType "proceedings-article" @default.
- W4385187369 hasAuthorship W4385187369A5032370728 @default.
- W4385187369 hasAuthorship W4385187369A5059418768 @default.
- W4385187369 hasAuthorship W4385187369A5091397373 @default.
- W4385187369 hasAuthorship W4385187369A5091947030 @default.
- W4385187369 hasConcept C119857082 @default.
- W4385187369 hasConcept C121332964 @default.
- W4385187369 hasConcept C12267149 @default.
- W4385187369 hasConcept C12713177 @default.
- W4385187369 hasConcept C136389625 @default.
- W4385187369 hasConcept C154945302 @default.
- W4385187369 hasConcept C163258240 @default.
- W4385187369 hasConcept C16910744 @default.
- W4385187369 hasConcept C169258074 @default.
- W4385187369 hasConcept C199360897 @default.
- W4385187369 hasConcept C41008148 @default.
- W4385187369 hasConcept C43214815 @default.
- W4385187369 hasConcept C50644808 @default.
- W4385187369 hasConcept C62520636 @default.
- W4385187369 hasConcept C66402592 @default.
- W4385187369 hasConcept C70153297 @default.
- W4385187369 hasConceptScore W4385187369C119857082 @default.
- W4385187369 hasConceptScore W4385187369C121332964 @default.
- W4385187369 hasConceptScore W4385187369C12267149 @default.
- W4385187369 hasConceptScore W4385187369C12713177 @default.
- W4385187369 hasConceptScore W4385187369C136389625 @default.
- W4385187369 hasConceptScore W4385187369C154945302 @default.
- W4385187369 hasConceptScore W4385187369C163258240 @default.
- W4385187369 hasConceptScore W4385187369C16910744 @default.
- W4385187369 hasConceptScore W4385187369C169258074 @default.
- W4385187369 hasConceptScore W4385187369C199360897 @default.
- W4385187369 hasConceptScore W4385187369C41008148 @default.
- W4385187369 hasConceptScore W4385187369C43214815 @default.
- W4385187369 hasConceptScore W4385187369C50644808 @default.
- W4385187369 hasConceptScore W4385187369C62520636 @default.
- W4385187369 hasConceptScore W4385187369C66402592 @default.
- W4385187369 hasConceptScore W4385187369C70153297 @default.
- W4385187369 hasLocation W43851873691 @default.
- W4385187369 hasOpenAccess W4385187369 @default.
- W4385187369 hasPrimaryLocation W43851873691 @default.
- W4385187369 hasRelatedWork W2979979539 @default.
- W4385187369 hasRelatedWork W3004897296 @default.
- W4385187369 hasRelatedWork W3127425528 @default.
- W4385187369 hasRelatedWork W3195168932 @default.
- W4385187369 hasRelatedWork W4288057626 @default.
- W4385187369 hasRelatedWork W4308191010 @default.
- W4385187369 hasRelatedWork W4311106074 @default.
- W4385187369 hasRelatedWork W4327531511 @default.
- W4385187369 hasRelatedWork W4327831767 @default.
- W4385187369 hasRelatedWork W4361795583 @default.
- W4385187369 isParatext "false" @default.
- W4385187369 isRetracted "false" @default.
- W4385187369 workType "article" @default.