Establishing news credibility using sentiment analysis on twitter

被引:0
|
作者
Sharf Z. [1 ,3 ]
Jalil Z. [2 ]
Amir W. [2 ]
Siddiqui N. [3 ]
机构
[1] Department of Computer Science, SZABIST, Karachi
[2] Department of Computer Science, International Islamic University Islamabad, Islamabad
来源
International Journal of Advanced Computer Science and Applications | 2019年 / 10卷 / 09期
关键词
Opinion mining; Sentiment analysis; Tweets;
D O I
10.14569/ijacsa.2019.0100927
中图分类号
学科分类号
摘要
The widespread use of Internet has resulted in a massive number of websites, blogs and forums. People can easily discuss with each other about different topics and products, and can leave reviews to help out others. This automatically leads to a necessity of having a system that may automatically extract opinions from those comments or reviews to perform a strong analysis. So, it may help out businesses to know the opinions of people about their products/services so they can make further improvements. Sentiment Analysis or Opinion Mining is the system that intelligently performs classification of sentiments by extracting those opinions or sentiments from the given text (or comments or reviews). This paper presents a thorough research work carried out on tweets' sentiment analysis. An area-specific analysis is done to determine the polarity of extracted tweets for make an automatic classification that what recent news people have liked or disliked. The research is further extended to perform retweet analysis to describe the re-distribution of reactions on a specific twitter post (or tweet). © 2018 The Science and Information (SAI) Organization Limited.
引用
收藏
页码:209 / 221
页数:12
相关论文
共 50 条
  • [1] Establishing News Credibility using Sentiment Analysis on Twitter
    Sharf, Zareen
    Jalil, Zakia
    Amir, Wajiha
    Siddiqui, Nudrat
    INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS, 2019, 10 (09) : 209 - 221
  • [2] Predicting Stock Movement using Sentiment Analysis of Twitter Feed
    Chakraborty, Pranjal
    Pria, Ummay Sani
    Rony, Md Rashad Al Hasan
    Majumdar, Mahbub Alam
    2017 6TH INTERNATIONAL CONFERENCE ON INFORMATICS, ELECTRONICS AND VISION & 2017 7TH INTERNATIONAL SYMPOSIUM IN COMPUTATIONAL MEDICAL AND HEALTH TECHNOLOGY (ICIEV-ISCMHT), 2017,
  • [3] SASM: A Tool for Sentiment Analysis on Twitter
    Onifade, O. F. W.
    Malik, M. A.
    2015 2ND WORLD SYMPOSIUM ON WEB APPLICATIONS AND NETWORKING (WSWAN), 2015,
  • [4] Twitter Sentiment Analysis using Various Classification Algorithms
    Deshwal, Ajay
    Sharma, Sudhir Kumar
    2016 5TH INTERNATIONAL CONFERENCE ON RELIABILITY, INFOCOM TECHNOLOGIES AND OPTIMIZATION (TRENDS AND FUTURE DIRECTIONS) (ICRITO), 2016, : 251 - 257
  • [5] Twitter Sentiment Analysis using Deep Neural Network
    Wazery, Yaser Maher
    Mohammed, Hager Saleh
    Houssein, Essam Halim
    2018 14TH INTERNATIONAL COMPUTER ENGINEERING CONFERENCE (ICENCO), 2018, : 177 - 182
  • [6] A SURVEY OF TWITTER SENTIMENT ANALYSIS
    Anuprathibha, T.
    Selvib, C. S. Kanimozhi
    IIOAB JOURNAL, 2016, 7 (09) : 374 - 378
  • [7] Sentiment Analysis of Twitter Data
    Desai, Radhi D.
    PROCEEDINGS OF THE 2018 SECOND INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTING AND CONTROL SYSTEMS (ICICCS), 2018, : 114 - 117
  • [8] Sentiment Analysis of Twitter Data
    El Rahman, Sahar A.
    AlOtaibi, Feddah Alhumaidi
    AlShehri, Wejdan Abdullah
    2019 INTERNATIONAL CONFERENCE ON COMPUTER AND INFORMATION SCIENCES (ICCIS), 2019, : 336 - 339
  • [9] On adverse drug event extractions using twitter sentiment analysis
    Moh M.
    Moh T.-S.
    Peng Y.
    Wu L.
    Network Modeling Analysis in Health Informatics and Bioinformatics, 2017, 6 (1)
  • [10] Sentiment Analysis of Top Colleges in India Using Twitter Data
    Mamgain, Nehal
    Mehta, Ekta
    Mittal, Ankush
    Bhatt, Gaurav
    2016 INTERNATIONAL CONFERENCE ON COMPUTATIONAL TECHNIQUES IN INFORMATION AND COMMUNICATION TECHNOLOGIES (ICCTICT), 2016,