SocFeedViewer: A Novel Visualization Technique for Social News Feeds Summarization on Large-Scale Social Network Services
Date Issued
2011
Date
2011
Author(s)
Chen, Yu-Jen
Abstract
Online social network services such as Facebook and Twitter have become increasingly popular. More and more users are accustomed to regularly reading the latest news feeds and interacting with friends on these social websites. However, when the numbers of friends and subscribed pages increase to a large extent, users will receive hundreds of messages in a day and will be overwhelmed by the information overload. To alleviate this problem, we propose a novel visualization technique for social news feeds summarization on large-scale social web services. The proposed system SocFeedViewer can produce an egocentric network graph based on the news feeds generated in an arbitrary period of time. This graph provides an overview of those who have generated news feeds during this time period. To enhance the reading experience, we incorporate community detection, connectivity analysis, and importance analysis into our system to make users capable of preferentially surfing news feeds that are more significant and interesting. We implement a real-world application and use the real social data of several volunteers to verify the usefulness of SocFeedViewer.
Subjects
News Feed Summarization
Egocentric Network Graph
Visualization Technique
Social Network Service
Type
thesis
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