Discovering Emerging Topics from WWW

Discovering Emerging Topics from WWW

Discovering emerging topics from WWW has been attracting attention of business professionals, especially marketing researchers. For this purpose, WWW can be a valuable source of information because it reflects the dynamics of human society. In this paper we aim at revealing the structure of WWW by using KeyGraph, a visualization method of hidden structure behind data, for understanding emerging...

Discovery of Emerging Topics between Communities on WWW

In the real world, discovering new topics covering profitable items and ideas (e.g., mobile phone, global warming, human genome project, etc) is important and interesting. However, since we cannot completely encode the world surrounding us, it’s difficult to detect such topics and their mechanisms in advance. In order to support the detection, we show a method for revealing the structure of WWW...

A Survey on Anomaly Detection for Discovering Emerging Topics

This paper identifies various concepts involved in social networks for finding the emerging topics. We focus on the various methods that can be applied for detecting the anomaly. The methods used are Hidden Markov Model, UMass Approach, CMU Approach, Change Finder method and Finite Mixture Model. These methods involve texts, videos, audios, URLs and mentions which are shared in the social netwo...

Discovering Emerging Graph Patterns from Chemicals

TwiInsight: Discovering Topics and Sentiments from Social Media Datasets

Social media platforms contain a great wealth of information which provides opportunities for us to explore hidden patterns or unknown correlations, and understand people’s satisfaction with what they are discussing. As one showcase, in this paper, we present a system, TwiInsight which explores the insight of Twitter data. Different from other Twitter analysis systems, TwiInsight automatically ...