Paper Info
Title
Identify Emergent Trends Based on the Blogosphere
Abstract
Information about upcoming trends is a valuable knowledge for both, companies and individuals. Detecting trends for a certain topic is of special interest. According to the latest information over 200 million blogs exist in the World Wide Web. Hence, every day millions of posts are published. These blogs contain an enormous think tank of open-source intelligence. Considering the continuously growing nature of the World Wide Web a primary factor of success is the ability to include the latest data and focus on the complete data set of blogs. The structured as well as unstructured data of blogs are available offline via a single database for further analyses. This paper describes and evaluates an algorithm to detect trends based on the data published in blog posts.
Year
DOI
Venue
2013
10.1109/WI-IAT.2013.147
IAT), 2013 IEEE/WIC/ACM International Joint Conferences
Keywords
Field
DocType
Web sites,World Wide Web,blog posts,blogosphere,emergent trend identification,open-source intelligence,trend detection,Blog,Social Media,Trend Detection,Web Mining
Data science,World Wide Web,Web intelligence,Web mining,Social media,Trend detection,Unstructured data,Engineering,Blogosphere,Special Interest Group
Conference
Volume
ISBN
Citations 
3
978-1-4799-2902-3
4
PageRank 
References 
Authors
0.58
3
3
Name
Order
Citations
PageRank
Patrick Hennig1147.38
Philipp Berger2178.14
Christoph Meinel32341319.90