Urdu Sentiment Analysis

被引:0
|
作者
Khan, Khairullah [1 ]
Rahman, Atta Ur [1 ]
Khan, Aurangzeb [1 ]
Khan, Ashraf Ullah [1 ]
Saqia, Bibi [1 ]
Khan, Wahab [2 ]
Khans, Asfandyar [3 ]
机构
[1] Univ Sci & Technol Bannu, Dept Comp Sci, Bannu, Pakistan
[2] Int Islamic Univ, Dept Comp Sci & Software Engn, Islamabad, Pakistan
[3] Univ Agr Peshawar, Inst Business & Management Sci, Peshawar, Pakistan
关键词
Urdu; sentiment analysis; social media; survey;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Internet is the most significant source of getting up thoughts, surveys for a product, and reviews for any type of service or activity. A Bulky amount of reviews are produced on daily basis on the cyberspace about online products and objects. For example, many individuals share their remarks, reviews and feelings in their own language utilizing social media networks such as twitter and so on. Considering their colossal Quantity and size, it is exceedingly knotty to look at with and interpret specified surveys. Sentiment Analysis (SA) aims at extracting people's opinion, felling and thought from their reviews in social websites. SA has recently gained significant consideration, however the vast majority of the resources and frameworks constructed so far are tailored to English as well as English like Western languages. The requirement for designing frameworks for different dialects is expanding, particularly as blogging and micro-blogging sites are becoming popular. This paper presents a comprehensive review of approaches of Urdu sentiment analysis and outlines of relevant gaps in the literature.
引用
收藏
页码:646 / 651
页数:6
相关论文
共 50 条
  • [21] Urdu Sentiment Analysis Using Supervised Machine Learning Approach
    Mukhtar, Neelam
    Khan, Mohammad Abid
    [J]. INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE, 2018, 32 (02)
  • [22] Effective lexicon-based approach for Urdu sentiment analysis
    Mukhtar, Neelam
    Khan, Mohammad Abid
    [J]. ARTIFICIAL INTELLIGENCE REVIEW, 2020, 53 (04) : 2521 - 2548
  • [23] Resource Creation and Evaluation of Aspect Based Sentiment Analysis in Urdu
    Rani, Sadaf
    Anwar, Muhammad Waqas
    [J]. AACL-IJCNLP 2020: THE 1ST CONFERENCE OF THE ASIA-PACIFIC CHAPTER OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS AND THE 10TH INTERNATIONAL JOINT CONFERENCE ON NATURAL LANGUAGE PROCESSING: PROCEEDINGS OF THE STUDENT RESEARCH WORKSHOP, 2020, : 72 - 77
  • [24] Sentiment analysis with word-based Urdu speech recognition
    Shaik, Riyaz
    Venkatramaphanikumar, S.
    [J]. JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING, 2021, 13 (5) : 2511 - 2531
  • [25] Sentiment Analysis for a Resource Poor Language-Roman Urdu
    Mehmood, Khawar
    Essam, Daryl
    Shafi, Kamran
    Malik, Muhammad Kamran
    [J]. ACM TRANSACTIONS ON ASIAN AND LOW-RESOURCE LANGUAGE INFORMATION PROCESSING, 2020, 19 (01)
  • [26] Sentiment Analysis for Urdu News Tweets Using Decision Tree
    Bibi, Raheela
    Qamar, Usman
    Ansar, Munazza
    Shaheen, Asma
    [J]. 2019 IEEE/ACIS 17TH INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING RESEARCH, MANAGEMENT AND APPLICATIONS (SERA), 2019, : 66 - 70
  • [27] Identification and handling of intensifiers for enhancing accuracy of Urdu sentiment analysis
    Mukhtar, Neelam
    Khan, Mohammad Abid
    Chiragh, Nadia
    Nazir, Shah
    [J]. EXPERT SYSTEMS, 2018, 35 (06)
  • [28] Opinion within Opinion: Segmentation Approach for Urdu Sentiment Analysis
    Hassan, Muhammad
    Shoaib, Muhammad
    [J]. INTERNATIONAL ARAB JOURNAL OF INFORMATION TECHNOLOGY, 2018, 15 (01) : 21 - 28
  • [29] Sentiment analysis with word-based Urdu speech recognition
    Riyaz Shaik
    S. Venkatramaphanikumar
    [J]. Journal of Ambient Intelligence and Humanized Computing, 2022, 13 : 2511 - 2531
  • [30] Discriminative Feature Spamming Technique for Roman Urdu Sentiment Analysis
    Mehmood, Khawar
    Essam, Daryl
    Shafi, Kamran
    Malik, Muhammad Kamran
    [J]. IEEE ACCESS, 2019, 7 : 47991 - 48002