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Cross usage of articles and tweets on author identification

机译:文章和推文在作者识别上的交叉使用

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The identities of the authors who having phenomenon with their sharings without revealing his/her identity on Twitter which is the most popular microblogging site, are wondered. The sharings of a Twitter account can be used to detect the identity of the user. Especially, a columnist who have written articles on various media organs, even if he/she does not reveal his/her identity, can be guessed. We tried to guess the author of an account by comparing the articles and sharings on Twitter accounts of 10 columnists. We performed tests firstly by taking each tweet as an individual text, and then grouping the specific number of tweets. We perceived that using the grouped tweet texts gives more accurate results than using each tweet individually. Additionally, we caught that we can guess the owner of a Twitter account with a good accuracy rate by comparing the sharings of this account and the articles of the candidate authors. We used the words themselves, their stems and 3-grams for digitizing of the texts. We achieved the most successful results with support vector machines from among several classifiers.
机译:对于那些在分享中有现象却没有在最受欢迎的微博网站Twitter上透露自己身份的作者的身份感到好奇。 Twitter帐户的共享可用于检测用户身份。尤其是,即使在没有透露自己身份的情况下,也会猜出在各种媒体机构上发表过文章的专栏作家。我们试图通过比较文章和10位专栏作家在Twitter帐户上的分享来猜测一个帐户的作者。我们首先通过将每个tweet作为单独的文本,然后将特定数量的tweet分组来进行测试。我们认为,与单​​独使用每个推文相比,使用分组推文文本可获得更准确的结果。另外,我们发现,通过比较该帐户的共享内容和候选作者的文章,我们可以猜出一个Twitter帐户的拥有者的准确率很高。我们使用单词本身,其词干和3克语法来对文本进行数字化。我们使用了多个分类器中的支持向量机,获得了最成功的结果。

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