Advanced Issues on Topic Detection, Tracking, and Trend Analysis for Social Multimedia

Topic Detection and Tracking within Social Networks

Topic Detection, Tracking, and Trend Analysis Using Self-Organizing Neural Networks

We address the problem of Topic Detection and Tracking (TDT) and subsequently detecting trends from a stream of text documents. Formulating TDT as a clustering problem in a class of self-organizing neural networks, called the Adaptive Resonance Theory (ART) networks, we propose an incremental algorithm to solve this clustering problem. From the topics being detected and tracked, we show how tre...

Topic Trend Detection in Newsgroups

In this paper we report on a project for Corporate Technology of Siemens AG, Munich, which aimed at the use of a social network analysis approach for trend and trend shift detection over time in a technically oriented newsgroup on mobile phones. The analysis was based on the assumption that a trend shift is relevant only if relevant (central) members of the newsgroup initiated this shift. A shi...

On-line Trend Analysis with Topic Models: \#twitter Trends Detection Topic Model Online

We present a novel topic modelling-based methodology to track emerging events in microblogs such as Twitter. Our topic model has an in-built update mechanism based on time slices and implements a dynamic vocabulary. We first show that the method is robust in detecting events using a range of datasets with injected novel events, and then demonstrate its application in identifying trending topics...

Novelty detection for topic tracking

Multi-source web news portals provide various advantages such as richness in news content and an opportunity to follow developments from different perspectives. However, in such environments, news variety and quantity can have an overwhelming effect. New event detection and topic tracking studies address this problem. They examine news streams and organize stories according to their events; how...