A survey of extremism online content analysis and prediction techniques in twitter based on sentiment analysis
Author:
Publisher
Springer Science and Business Media LLC
Subject
Law,Strategy and Management,Safety Research
Link
https://link.springer.com/content/pdf/10.1057/s41284-022-00335-4.pdf
Reference69 articles.
1. Abrar, M.F., M.S. Arefin, and M.S. Hossain. 2019. A framework for analysing real-time tweets to detect terrorist activities. Proceedings of International Conference on Electrical, Computer and Communication Engineering. https://doi.org/10.1109/ECACE.2019.8679430.
2. Adek, and Bustami Ula. 2021. Systematics review on the application of social media analytics for detecting radical and extremist group. Materials Science and Engineering 1071: 012029. https://doi.org/10.1088/1757-899X/1071/1/012029.
3. Ahmad, Shakeel, Muhammad Zubair Asghar, Fahad M. Alotaibi, and Irfanullah Awan. 2019. Detection and classification of social media-based extremist affiliations using sentiment analysis techniques. Human Centric Computing and Information Sciences. https://doi.org/10.1186/s13673-019-0185-6.
4. Aleroud, Ahmed, Nisreen Abu-Alsheeh, and Emad Al-Shawakfa. 2020. A graph proximity feature augmentation approach for identifying accounts of terrorists on twitter. Computers and Security 99: 102056. https://doi.org/10.1016/j.cose.2020.102056.
5. Al-Khalisy, Muhanad A. E., and Hashem B. Jehlol. 2018. Terrorist affiliations identifying through twitter social media analysis using data mining and web mapping techniques. Journal of Engineering and Applied Sciences 13: 7459–7464. https://doi.org/10.36478/jeasci.2018.7459.7464.
Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. CIDER: Context-sensitive polarity measurement for short-form text;PLOS ONE;2024-04-18
2. Investigating long short‐term memory approach for extremist messages detection in Kazakh language;Expert Systems;2024-03-27
3. Detection of fake reviewer groups in product reviews using novel bidirectional encoder revolutionary transformer compared with stochastic gradient descent;AIP Conference Proceedings;2024
4. Enhanced Extremist Reviewer Group Detection in Online Product Reviews using RNN in comparison with CNN;2023 9th International Conference on Smart Structures and Systems (ICSSS);2023-11-23
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3