利用机器学习检测假新闻

Sneha Sanghpriy Moon, Akshata Lonare, Aditi Chandekar, Mayuri Khandre, Prof. Mahesh Dumbere
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引用次数: 0

摘要

大多数智能手机用户喜欢通过互联网社交媒体阅读新闻。新闻网站发布新闻并提供认证来源。问题是如何验证在 WhatsApp 群组、Facebook 页面、Twitter 及其他微博客和社交网站等社交媒体中传播的新闻和文章。相信谣言和冒充新闻对社会有害无益。当务之急是制止谣言,尤其是在印度这样的发展中国家,并关注正确、真实的新闻报道。本文展示了一种假新闻检测模型和方法。在机器学习和自然语言处理的帮助下,本文尝试汇总新闻,然后使用支持向量机确定新闻的真假。建议模型的结果与现有模型进行了比较。所提出的模型运行良好,结果的正确率高达 93.6%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fake News Detection using Machine Learning
Most of the smart phone users prefer to read the news via social media over internet. The news websites are publishing the news and provide the source of authentication. The question is how to authenticate the news and articles which are circulated among social media like WhatsApp groups, Facebook Pages, Twitter and other micro blogs & social networking sites. It is harmful for the society to believe on the rumors and pretend to be a news. The need of an hour is to stop the rumors especially in the developing countries like India, and focus on the correct, authenticated news articles. This paper demonstrates a model and the methodology for fake news detection. With the help of Machine learning and natural language processing, it is tried to aggregate the news and later determine whether the news is real or fake using Support Vector Machine. The results of the proposed model is compared with existing models. The proposed model is working well and defining the correctness of results upto 93.6% of accuracy
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