Text Mining for News and Blogs Analysis
- (Berendt, 2017) ⇒ Bettina Berendt. (2017). "Text Mining for News and Blogs Analysis". In: (Sammut & Webb, 2017).
- QUOTE: News and blogs are temporally indexed online texts and play a key role in today's information distribution and consumption. News communicate selected information on current events, written by professional or citizen journalists; blogs are updated publications on the Web that span a much wider range of topics, styles, and authors. Particularly important in recent years have been microblogs such as Twitter. The entry gives an overview of how text mining (for tasks such as description, classification, prediction, search, recommendation, or summarization) is applied to analyze the textual parts of news and blogs, extracting topics, events, opinions, sentiments, and other aspects of content. Often, textual analysis is complemented by the analysis of further data such as the social network of authors and readers. The properties of news and blogs data structures and language use require methods for preprocessing and analyzing that are tailored to news and (micro)blogs, and the tasks often profit from an interactive approach in which the user plays an active role in sensemaking. The methods are deployed in a wide range of applications and services.