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  • Open Access

    ARTICLE

    Sentiment Analysis Based on Performance of Linear Support Vector Machine and Multinomial Naïve Bayes Using Movie Reviews with Baseline Techniques

    Mian Muhammad Danyal1, Sarwar Shah Khan2,4, Muzammil Khan2,*, Muhammad Bilal Ghaffar1, Bilal Khan1, Muhammad Arshad3

    Journal on Big Data, Vol.5, pp. 1-18, 2023, DOI:10.32604/jbd.2023.041319

    Abstract Movies are the better source of entertainment. Every year, a great percentage of movies are released. People comment on movies in the form of reviews after watching them. Since it is difficult to read all of the reviews for a movie, summarizing all of the reviews will help make this decision without wasting time in reading all of the reviews. Opinion mining also known as sentiment analysis is the process of extracting subjective information from textual data. Opinion mining involves identifying and extracting the opinions of individuals, which can be positive, neutral, or negative. The… More >

  • Open Access

    ARTICLE

    COVID-19 Public Sentiment Insights: A Text Mining Approach to the Gulf Countries

    Saleh Albahli1, Ahmad Algsham1, Shamsulhaq Aeraj1, Muath Alsaeed1, Muath Alrashed1, Hafiz Tayyab Rauf2,*, Muhammad Arif3, Mazin Abed Mohammed4

    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1613-1627, 2021, DOI:10.32604/cmc.2021.014265

    Abstract Social media has been the primary source of information from mainstream news agencies due to the large number of users posting their feedback. The COVID-19 outbreak did not only bring a virus with it but it also brought fear and uncertainty along with inaccurate and misinformation spread on social media platforms. This phenomenon caused a state of panic among people. Different studies were conducted to stop the spread of fake news to help people cope with the situation. In this paper, a semantic analysis of three levels (negative, neutral, and positive) is used to gauge… More >

  • Open Access

    ARTICLE

    Aspect-Based Sentiment Analysis for Polarity Estimation of Customer Reviews on Twitter

    Ameen Banjar1, Zohair Ahmed2, Ali Daud1, Rabeeh Ayaz Abbasi3, Hussain Dawood4,*

    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2203-2225, 2021, DOI:10.32604/cmc.2021.014226

    Abstract Most consumers read online reviews written by different users before making purchase decisions, where each opinion expresses some sentiment. Therefore, sentiment analysis is currently a hot topic of research. In particular, aspect-based sentiment analysis concerns the exploration of emotions, opinions and facts that are expressed by people, usually in the form of polarity. It is crucial to consider polarity calculations and not simply categorize reviews as positive, negative, or neutral. Currently, the available lexicon-based method accuracy is affected by limited coverage. Several of the available polarity estimation techniques are too general and may not reflect… More >

  • Open Access

    ARTICLE

    A Recommendation Approach Based on Product Attribute Reviews: Improved Collaborative Filtering Considering the Sentiment Polarity

    Min Cao1, Sijing Zhou1, Honghao Gao1,2,3

    Intelligent Automation & Soft Computing, Vol.25, No.3, pp. 595-604, 2019, DOI:10.31209/2019.100000114

    Abstract Recommender methods using reviews have become an area of active research in e-commerce systems. The use of auxiliary information in reviews as a way to effectively accommodate sparse data has been adopted in many fields, such as the product field. The existing recommendation methods using reviews typically employ aspect preference; however, the characteristics of product reviews are not considered adequate. To this end, this paper proposes a novel recommendation approach based on using product attributes to improve the efficiency of recommendation, and a hybrid collaborative filtering is presented. The product attribute model and a new More >

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