Title :
Kondenzer: Exploration and visualization of archived social media
Author :
Alonso, Omar ; Khandelwal, Kartikay
Author_Institution :
Microsoft Corp., Mountain View, CA, USA
fDate :
March 31 2014-April 4 2014
Abstract :
Modern social networks such as Twitter provide a platform for people to express their opinions on a variety of topics ranging from personal to global. While the factual part of this information and the opinions of various experts are archived by sources such as Wikipedia and reputable news articles, the opinion of the general public is drowned out in a sea of noise and “un-interesting” information. In this demo we present Kondenzer - an offline system for condensing, archiving and visualizing social data. Specifically, we create digests of social data using a combination of filtering, duplicate removal and efficient clustering. This gives a condensed set of high quality data which is used to generate facets and create a collection that can be visualized using the PivotViewer control.
Keywords :
data visualisation; information retrieval systems; social networking (online); Kondenzer; PivotViewer control; archived social media exploration; archived social media visualization; duplicate removal; efficient clustering; high quality data; social data archiving; social data condensing; social data visualization; social networks; Companies; Data visualization; Feature extraction; Media; Noise; Twitter;
Conference_Titel :
Data Engineering (ICDE), 2014 IEEE 30th International Conference on
Conference_Location :
Chicago, IL
DOI :
10.1109/ICDE.2014.6816741