Deceptive opinion spam detection approaches: a literature survey
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence
Link
https://link.springer.com/content/pdf/10.1007/s10489-022-03427-1.pdf
Reference138 articles.
1. Aghakhani H, Machiry A, Nilizadeh S, Kruegel C, Giovanni Vigna (2018) Detecting deceptive reviews using generative adversarial networks. In: 2018 IEEE security and privacy workshops (SPW), pp 89–95
2. Ahsan MNI, Nahian T, Kafi AA, Hossain MdI, Shah FM (2016) An ensemble approach to detect review spam using hybrid machine learning technique. In: 2016 19th International conference on computer and information technology (ICCIT). IEEE, pp 388–394
3. Akoglu L, Chandy R, Faloutsos C (2013) Opinion fraud detection in online reviews by network effects. ICWSM 13(2–11):29
4. Algur SP, Patil AP, Hiremath PS, Shivashankar S (2010) Conceptual level similarity measure based review spam detection. In: 2010 International conference on signal and image processing. IEEE, pp 416–423
5. Archchitha K, Charles EYA (2019) Opinion spam detection in online reviews using neural networks. In: 2019 19th International conference on advances in ICT for emerging regions (ICTer), vol 250. IEEE, pp 1–6
Cited by 15 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. PSC-BERT: A spam identification and classification algorithm via prompt learning and spell check;Knowledge-Based Systems;2024-10
2. Investigating the optimal number of topics by advanced text-mining techniques: Sustainable energy research;Engineering Applications of Artificial Intelligence;2024-10
3. Fake review detection techniques, issues, and future research directions: a literature review;Knowledge and Information Systems;2024-05-17
4. Experimental Analysis of Polishing of Hybrid Aluminium Metal Matrix Composite Reinforced with SiC, ZrO2, and NiTi Particles Using a Developed Rotary Abrasive Float Polishing System;International Journal of Precision Engineering and Manufacturing;2024-05-06
5. Detection System Based on Text Adversarial and Multi-Information Fusion for Inappropriate Comments in Mobile Application Reviews;Electronics;2024-04-10
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