Product review opinion based on sentiment analysis

被引:2
|
作者
Purohit, Amit [1 ]
Patheja, Pushpinder Singh [1 ]
机构
[1] Vellore Inst Technol VIT Bhopal, Indore Rd, Bhopal 466114, Madhya Pradesh, India
关键词
Sentiment analysis; opinion mining; support vector machine; thematic analysis;
D O I
10.3233/JIFS-213296
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Sentiment analysis is a natural language processing (NLP) technique for determining emotional tone in a body of text. Using product reviews in sentiment analysis and opinion mining various methods have been developed previously. Although, existing product review analyzing techniques could not accurately detect the product aspect and non-aspect. Hence a novel Detach Frequency Assort is proposed to detect the product aspect term using TF-ISF (Term frequency-inverse sentence frequency) with Part of Speech (POS) tags for sentence segmentation and additionally using Feedback Neural Network to combine product aspect feedback loop. Furthermore, decision-making problem occurs during classification of sentiments. Hence, to solve this problem a novel technique named, Systemize Polarity Shift is proposed in which flow search based Support Vector Machine (SVM) with Bag of Words model classifies pre-trained review comments as positive, negative, and neutral sentiments. Moreover, the identification of specific products is not focused in sentiment analysis. Hence, a novel Revival Extraction is proposed in which a specific product is extracted based on thematic analysis method to obtain accurate data. Thus, the proposed Product Review Opinion framework gives effective optimized results in sentiment analysis with high accuracy, specificity, recall, sensitivity, F1-Score, and precision.
引用
收藏
页码:3153 / 3169
页数:17
相关论文
共 50 条
  • [1] SAMIKSHA - Sentiment Based Product Review Analysis System
    Potdar, Aarti
    Patil, Pranav
    Bagla, Raunak
    Pandey, Rohitashwa
    Jadhav, Nagesh
    1ST INTERNATIONAL CONFERENCE ON INFORMATION SECURITY & PRIVACY 2015, 2016, 78 : 513 - 520
  • [2] Fuzzy Logic Based Sentiment Analysis of Product Review Documents
    Indhuja, K.
    Raj, Reghu P. C.
    2014 FIRST INTERNATIONAL CONFERENCE ON COMPUTATIONAL SYSTEMS AND COMMUNICATIONS (ICCSC), 2014, : 18 - 22
  • [3] Sentiment Analysis of Product Reviews: A Review
    Shivaprasad, T. K.
    Shetty, Jyothi
    PROCEEDINGS OF THE 2017 INTERNATIONAL CONFERENCE ON INVENTIVE COMMUNICATION AND COMPUTATIONAL TECHNOLOGIES (ICICCT), 2017, : 298 - 303
  • [4] Product Opinion Mining Using Sentiment Analysis on Smartphone Reviews
    Chawla, Shilpi
    Dubey, Gaurav
    Rana, Ajay
    2017 6TH INTERNATIONAL CONFERENCE ON RELIABILITY, INFOCOM TECHNOLOGIES AND OPTIMIZATION (TRENDS AND FUTURE DIRECTIONS) (ICRITO), 2017, : 377 - 383
  • [5] SENTIMENT ANALYSIS ON PRODUCT REVIEW: A SURVEY
    Ezhilarasan, M.
    Govindasamy, V
    Akila, V
    Vadivelan, K.
    2019 8TH IEEE INTERNATIONAL CONFERENCE ON COMPUTATION OF POWER, ENERGY, INFORMATION AND COMMUNICATION (ICCPEIC'19), 2019, : 180 - 192
  • [6] Opinion Mining and Sentiment Analysis on Online Customer Review
    Kumar, Santhosh K. L.
    Desai, Jayanti
    Majumdar, Jharna
    2016 IEEE INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND COMPUTING RESEARCH, 2016, : 552 - 555
  • [7] Sentiment analysis using product review data
    Fang X.
    Zhan J.
    Journal of Big Data, 2015, 2 (01)
  • [8] Topic Model Based Opinion Mining and Sentiment Analysis
    Krishna, Vamshi B.
    Pandey, Ajeet Kumar
    Kumar, Siva A. P.
    2018 INTERNATIONAL CONFERENCE ON COMPUTER COMMUNICATION AND INFORMATICS (ICCCI), 2018,
  • [9] Classifying product reviews from balanced datasets for Sentiment Analysis and Opinion Mining
    Sudhakaran, Periakaruppan
    Hariharan, Shanmugasundaram
    Lu, Joan
    2014 6TH INTERNATIONAL CONFERENCE ON MULTIMEDIA, COMPUTER GRAPHICS AND BROADCASTING (MULGRAB), 2014, : 29 - 34
  • [10] Product weakness finder: an opinion-aware system through sentiment analysis
    Wang, Hongwei
    Wang, Wei
    INDUSTRIAL MANAGEMENT & DATA SYSTEMS, 2014, 114 (08) : 1301 - 1320