Research on the Detection and Tracking of Hot Event in Microblogs Based on the Analysis of Mood Features

DOI

10.2991/scict-14.2014.1How to use a DOI?

Keywords

mood words; grained emotion; microblog; hot events; detection; tracking

Abstract

With the widespread application of microblog, it has become a platform for people to publish their interest topics, to express personal feelings, to participate in a centralized discussion. Aiming at the tracking problem of hot events in microblogs, this paper proposes a new tracking method of hot events in microblogs based on the analysis of the features of mood information that is the total amount of emotion value and its growth rate. The experiment is carried to verify the feasibility of the method by the real-time capture and analysis of microblogs correlating with the hot events in different periods. Experimental results show that the method based on analyzing the features of mood information can effectively identify hot topic in microblogs.

Copyright

© 2014, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Gaofeng Huang
AU  - Xueguang Zhou
PY  - 2014/05
DA  - 2014/05
TI  - Research on the Detection and Tracking of Hot Event in Microblogs Based on the Analysis of Mood Features
BT  - Proceedings of the 2nd International Conference on Soft Computing in Information Communication Technology
PB  - Atlantis Press
SP  - 1
EP  - 5
SN  - 1951-6851
UR  - https://doi.org/10.2991/scict-14.2014.1
DO  - 10.2991/scict-14.2014.1
ID  - Huang2014/05
ER  -