On social media, words and phrases reflect people's opinions about certain goods, services, organisations, laws, and events. In the discipline of NLP, the objective of sentiment analysis is to extract positive things or negative things from social media. Researchers are driven to complete their sentiment analysis research because of the government and corporate organisations' and individuals' exponentially growing needs. This study optimises sentimental analysis using four cutting-edge machine learning classifiers: Naivebayes, J48, BFTree, and OneR. This four classification methods' effectiveness are investigated and contrasted. While OneR appears more promise in producing the accuracy of correctly classified instances, Naivebayes was proven to be quick at learning. This study has observed that the four records are positively related, and the product's position in online market has also advanced over time. In light of the analysis of the favourable reviews and star ratings, this research study has suggested displaying a potentially successful or disastrous item based on the positive surveys. Finally, the relationship between the quantity of surveys and star ratings are also analyzed.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Optimized Sentiment Analysis of Hotel Reviews using Machine Learning Algorithms


    Contributors:


    Publication date :

    2022-12-01


    Size :

    682195 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Expression of Concern for: Optimized Sentiment Analysis of Hotel Reviews using Machine Learning Algorithms

    Navanith, D / Likhith, Kona / Vardhan, Mandaloju Sai et al. | IEEE | 2022

    Free access

    Efficient Machine Leaning Algorithms for Sentiment Analysis In Car Rental Service

    Nayak, Smitha / Sonia / Sharma, Yogesh Kumar | IEEE | 2023


    Sentiment analysis based product rating using textual reviews

    Sindhu, C / Vyas, Dyawanapally Veda / Pradyoth, Kommareddy | IEEE | 2017


    Efficient Machine leaning algorithms for sentiment analysis in Car rental sevice

    Nayak, Smitha / Sonia / Sharma, Yogesh Kumar | IEEE | 2023


    Machine Learning based Twitter Sentiment Analysis on COVID-19

    K, Nirmala Devi / S, Shanthi / K, Hemanandhini et al. | IEEE | 2021