Sentiment Analysis of Music Criticism Based on Data Mining

DOI

10.2991/iceemr-18.2018.84How to use a DOI?

Keywords

commentary emotion mining, space vector model, musical emotion classification

Abstract

With the development of web2.0, more and more people like to express their emotions by making comments anytime and anywhere. Music comments are an emotional expression of the listener's mood for listening to songs. On the basis of the original Hevner emotion loop, this paper proposes an optimized emotional model that fits Chinese people's thinking and language habits, constructs a new musical sentiment dictionary, analyzes the polarity of musical emotions, and proposes an emotional vector space model based on emotional units. Through experiments, it is proved that the emotional vector space model has higher accuracy and convenience than artificial emotion annotation.

Copyright

© 2018, 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  - Yao Liang
AU  - Hu Wang
PY  - 2018/06
DA  - 2018/06
TI  - Sentiment Analysis of Music Criticism Based on Data Mining
BT  - Proceedings of the 2018 2nd International Conference on Education, Economics and Management Research (ICEEMR 2018)
PB  - Atlantis Press
SP  - 368
EP  - 371
SN  - 2352-5398
UR  - https://doi.org/10.2991/iceemr-18.2018.84
DO  - 10.2991/iceemr-18.2018.84
ID  - Liang2018/06
ER  -