Showing 41 - 60 results of 240 for search '"sentiment analysis"', query time: 0.06s Refine Results
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    Exploring Coevolution of Emotional Contagion and Behavior for Microblog Sentiment Analysis: A Deep Learning Architecture by Qi Zhang, Zufan Zhang, Maobin Yang, Lianxiang Zhu

    Published 2021-01-01
    “…This paper aims to explore coevolution of emotional contagion and behavior for microblog sentiment analysis. Accordingly, a deep learning architecture (denoted as MSA-UITC) is proposed for the target microblog. …”
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    Comparison of Naive Bayes and SVM Algorithms for Sentiment Analysis of PUBG Mobile on Google Play Store by Putri Ratna Sari, Dwi Rosa Indah, Errissya Rasywir, Mgs Afriyan firdaus, Ghita Athalina

    Published 2024-11-01
    “…However, a cursory examination of reviews may not fully capture the nuances of user sentiment, necessitating a more comprehensive sentiment analysis. This research will employ a positive and negative sentiment analysis of Indonesian PUBG Mobile reviews on the Google Play Store, utilizing a comparative approach to evaluate the performance of two algorithms: Naïve Bayes and Support Vector Machine (SVM). …”
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    Global Perspectives on Laptop Features: A Sentiment Analysis of User Preferences in Developed and Developing Countries by Mehrdad Maghsoudi, Mohammadreza Bakhtiari, Hamidreza Bakhtiari

    Published 2025-01-01
    “…This study examines laptop user sentiments across developed and developing countries using aspect-based sentiment analysis (ABSA) on social media data. Employing a mixed-methods approach, the research combines large-scale sentiment analysis of 1,467,535 tweets with expert insights gathered through a Delphi panel of ten industry professionals. …”
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    Comparative Analysis of TF-IDF and Word2Vec in Sentiment Analysis: A Case of Food Reviews by Zhan Zerui

    Published 2025-01-01
    “…Sentiment analysis is an important area of natural language processing that supports applications such as market analysis, customer feedback, and social media monitoring by identifying and classifying opinions in text. …”
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