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The Method of Support Vectors in the Analysis of Social Networks User Profiles

机译:社交网络用户资料分析中的支持向量法

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Sociological surveys and tests exist for a long period of time and help to explore humanity to identify their interests and desires but we live in a world where almost everyone has their own profile in the social networks where they post pictures, write thoughts, notes and so on. Popular social networks in Russia can be represented as an online environment which is used to facilitate social interactions such as content sharing, points of view, experience and relevant information. In this study, we consider the method of support vectors for analysis of users? profiles in social networks with the help of machine learning. We developed a system that could determine the selected network user opinion about the annexation of Crimea to Russia.
机译:社会学调查和测验存在很长时间,有助于探索人类以确定自己的兴趣和欲望,但我们生活在一个几乎每个人在社交网络中都有自己个人资料的世界,他们在社交网络上张贴图片,写思想,记录等。上。俄罗斯的流行社交网络可以表示为一种在线环境,用于促进社交互动,例如内容共享,观点,经验和相关信息。在这项研究中,我们考虑了支持向量的方法来分析用户?在机器学习的帮助下,社交网络中的个人资料。我们开发了一种系统,可以确定所选网络用户对克里米亚并购俄罗斯的看法。

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