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Early investigation of proposed hoax detection for decreasing hoax in social media

机译:旨在减少社交媒体中的恶作剧的恶作剧检测的早期调查

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摘要

Social Media allow people to communicate over long distance and increase the users for the past years. However the threat of Hoax is also increasing in social media which increase the risk of mass panic, where the society become confuse between false and true, other words between hoax and not hoax. To mitigate the effect of hoax, a system to filter out hoax posts from social media is proposed. We propose a system framework that might be able to filter out hoax from social media post feeds in order to reduce the amount of hoax posts in social media. It is difficult to reduce 100% hoax from social media, but at least there is a technology which can decrease the hoax in social media. This system works by utilizing data mining to search past hoax records and analyze the post data pattern to determine whether a post is a hoax or not hoax. Our proposed system will also utilize social media Application Program Interface (API) such as news, facebook, twitter, in order to find similar writing in other social media or news website to find out the authenticity of a person's post.
机译:社交媒体使人们可以进行长途通信,并在过去几年中增加了用户。然而,恶作剧的威胁也在社交媒体中增加,这增加了大规模恐慌的风险,在这种情况下,社会变得虚假与真实之间混淆,换句话说,恶作剧与非恶作剧之间变得混乱。为了减轻骗局的影响,提出了一种从社交媒体中过滤掉骗局帖子的系统。我们提出了一个系统框架,该系统框架可能能够从社交媒体帖子提要中过滤掉恶作剧,从而减少社交媒体中的恶作剧帖子数量。很难从社交媒体上减少100%的骗局,但至少有一项技术可以减少社交媒体上的骗局。该系统通过利用数据挖掘来搜索过去的骗局记录并分析帖子数据模式来确定帖子是否为骗局而起作用。我们提出的系统还将利用社交媒体应用程序接口(API)(例如新闻,facebook,twitter),以便在其他社交媒体或新闻网站中找到类似的文字,从而找出某人帖子的真实性。

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