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The Internet is a major source of online news content. Current efforts to evaluate online news content, including text, story line and sources is limited by the use of small-scale manual techniques that are time consuming and dependent on human judgments. This article explores the use of machine learning algorithms and mathematical techniques for Internet-scale data mining and semantic discovery of...
Marine incident reports available from official marine bodies contain a wealth of information about the type, causes of incident, and details on the sequence of events that lead to the incident. Knowledge discovery and retrieval of useful information through content analysis and text mining from such reports will help us to understand the primary/secondary causes for the incidents and establish the...
Collective intelligence refers to the intelligence that emerges from local interactions among individual people. In the last few decades, Web 2.0 technologies have enabled new forms of collective intelligence that allow massive numbers of loosely organized individuals to interact and create high quality intellectual artifacts. In computer and information science disciplines, automated computational...
In recent years, usage of social media websites have been soaring. This trend not only limits to personal but corporate web-sites. The latter platforms contain an enormous amount of data posted by customers or users. Without a surprise, the data in corporate social media web-sites are normally link to the products or services provided by the companies. Therefore, the data can be utilized for the sake...
Tor is a popular 'darknet', a network that aims to conceal its users' identities and online activities. Darknets are composed of host machines that cannot be accessed by conventional means, which is why the content they host is typically not indexed by traditional search engines like Google and Bing. On Tor, web content and other types of services can anonymously be made available as so-called hidden...
This paper proposes a method employing text mining techniques to analyze e-mails collected at various source. The method inputs the subject and the body of an email and decides a text class for the e-mail. Also, the method extracts key concepts from e-mails and presents their statistical information. The results of numerical experiments indicate that acquired concept relation dictionaries correspond...
This paper presents an overview of past papers published at the CBMS symposiums from a content analysis point of view. A simple, yet effective word counting using Harvard Psycho-Social dictionary was used to estimate different aspects of sentiment that can be present even in scientific papers. Using simple statistics we uncover some of the very interesting trends in the last five CBMS symposiums....
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