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Comparative Analysis of Japan and the US Cybersecurity Related Newspaper Articles: A Content and Sentiment Analysis Approach

机译:日本与美国网络安全相关报纸论文的比较分析:内容与情感分析方法

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Recent advancements in the field of Information Technology (IT) have not only changed the way people consume news but also made it possible for researchers to analyze a plethora of news, especially when the headlines are changing every minute. Big data, Natural Language Processing (NLP) and Machine Learning (ML) techniques are becoming staple for researchers of every domain to discover patterns and themes in the vast amount of data. This research would utilize NPL and ML techniques to analyze cybersecurity-related newspaper articles of major newspapers (digital version) from Japan and the US. Japan and the US are close allies, and they are collaborating in the field of cybersecurity owing to its rising significance for nations. However, as the demography, culture, and political behavior are different in both countries, it would be fascinating and very critical to analyze how newspapers from both countries are dealing with cybersecurity issues.
机译:信息技术领域的最新进展(IT)不仅改变了人们消耗新闻的方式,而且研究人员可以分析一流的新闻,特别是当头条新闻正在改变每分钟时。 大数据,自然语言处理(NLP)和机器学习(ML)技术正在成为所有域的研究人员的主食,以发现在大量数据中发现模式和主题。 该研究将利用NPL和ML技术来分析来自日本和美国的网络安全相关报纸(数字版)的网络安全相关报纸章程。 日本和美国是密切的盟友,由于对国家的显着意义,他们在网络安全领域正在合作。 然而,在两国的人口统计学,文化和政治行为中,分析两个国家的报纸是如何处理网络安全问题,这将是令人着迷的,非常重要。

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