Real-Time Sentiment Analysis of Saudi Dialect Tweets Using SPARK

被引：0
|
作者：
Assiri, Adel [1 ]
Emam, Ahmed [1 ]
Al-dossari, Hmood [1 ]
机构：
[1] King Saud Univ, Dept Informat Syst, Riyadh, Saudi Arabia
来源：
2016 IEEE INTERNATIONAL CONFERENCE ON BIG DATA (BIG DATA) | 2016年
关键词：
big data; sentiment analytics; stream data; spark; flum;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In recent years the flow of Saudi dialect big data in social media has enforced different sentiment analysis techniques to know the trends of the Saudi users towards different issues and events. The currents techniques analyze this amount of data in off-line manner which can't support the real-time decision making in the critical issues. Real-time analytics on stream data have been given attention in different languages and different dialects such as English, which has not been given yet in Saudi dialect. Real-time aims to answer queries "right-now". In this work we intend to propose and develop a real-time solution for Saudi dialect in Twitter. The proposed solution supports the process of stream data in real time.
引用
收藏
页码：3947 / 3950
页数：4
相关论文
共 50 条
  • [1] Sentiment lexicon for sentiment analysis of Saudi dialect tweets
    Al-Thubaity, Abdulmohsen
    Alqahtani, Qubayl
    Aljandal, Abdulaziz
    [J]. ARABIC COMPUTATIONAL LINGUISTICS, 2018, 142 : 301 - 307
  • [2] Sentiment Analysis of Arabic Tweets in Smart Cities: A Review of Saudi Dialect
    Alotaibi, Shoayee
    Mehmood, Rashid
    Katib, Iyad
    [J]. 2019 FOURTH INTERNATIONAL CONFERENCE ON FOG AND MOBILE EDGE COMPUTING (FMEC), 2019, : 330 - 335
  • [3] Developing lexicon-based algorithms and sentiment lexicon for sentiment analysis of saudi dialect tweets
    Al-Ghaith, Waleed
    [J]. International Journal of Advanced Computer Science and Applications, 2019, 10 (11): : 83 - 88
  • [4] Developing Lexicon-based Algorithms and Sentiment Lexicon for Sentiment Analysis of Saudi Dialect Tweets
    Al-Ghaith, Waleed
    [J]. INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS, 2019, 10 (11) : 83 - 88
  • [5] Real Time Sentiment Analysis of Tweets Using Naive Bayes
    Goel, Ankur
    Gautam, Jyoti
    Kumar, Sitesh
    [J]. PROCEEDINGS ON 2016 2ND INTERNATIONAL CONFERENCE ON NEXT GENERATION COMPUTING TECHNOLOGIES (NGCT), 2016, : 257 - 261
  • [6] Sentiment Analysis of Arabic Jordanian Dialect Tweets
    Atoum, Jalal Omer
    Nouman, Mais
    [J]. INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS, 2019, 10 (02) : 256 - 262
  • [7] Sentiment Analysis of Saudi Dialect Using Deep Learning Techniques
    Alahmary, Rahma M.
    Al-Dossari, Hmood Z.
    Emam, Ahmed Z.
    [J]. 2019 INTERNATIONAL CONFERENCE ON ELECTRONICS, INFORMATION, AND COMMUNICATION (ICEIC), 2019, : 562 - 567
  • [8] Real-Time Sentiment Analysis of 2019 Election Tweets using Word2vec and Random Forest Model
    Hitesh, M. S. R.
    Vaibhav, Vedhosi
    Kalki, Y. J. Abhishek
    Kamtam, Suraj Harsha
    Kumari, Santoshi
    [J]. 2019 2ND INTERNATIONAL CONFERENCE ON INTELLIGENT COMMUNICATION AND COMPUTATIONAL TECHNIQUES (ICCT), 2019, : 146 - 151
  • [9] Emotional Analysis of Arabic Saudi Dialect Tweets Using a Supervised Learning Approach
    AlFutamani, Abeer A.
    Al-Baity, Heyam H.
    [J]. INTELLIGENT AUTOMATION AND SOFT COMPUTING, 2021, 29 (01): : 89 - 109
  • [10] Detecting Real-time Events using Tweets
    Sato, Koichi
    Wang, Junbo
    Cheng, Zixue
    [J]. PROCEEDINGS OF 2016 IEEE SYMPOSIUM SERIES ON COMPUTATIONAL INTELLIGENCE (SSCI), 2016,
12345