虚假的社交媒体新闻和扭曲的竞选检测框架使用情绪分析和机器学习
Akashdeep Bhardwaj1, Salil Bharany2, SeongKi Kim3
1School of Computer Science, University of Petroleum and Energy Studies, Dehradun, India.
Heliyon
|September 10, 2024
概括
这项研究引入了一种新的框架,使用基于情感的情感分析来检测社交媒体上的假新闻和机器人帐户. 该模型达到99.68%的准确性,超过了用于识别虚假信息活动的现有方法.
科学领域:
- 计算机科学 计算机科学
- 人工智能的人工智能
- 自然语言处理自然语言处理.
背景情况:
- 社交媒体平台促进了全球信息交换,但越来越多地被利用来传播假新闻和垃圾邮件.
- 手动验证大量社交媒体内容是不可行的,需要自动化解决方案.
- 现有的方法很难准确地区分真实的内容与虚假信息和恶意机器人活动.
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