Emotion evolutions of sub-topics about popular events on microblogs
| Published date | 07 August 2017 |
| DOI | https://doi.org/10.1108/EL-09-2016-0184 |
| Date | 07 August 2017 |
| Pages | 770-782 |
| Author | Qingqing Zhou,Chengzhi Zhang |
| Subject Matter | Information & knowledge management,Information & communications technology,Internet |
Emotion evolutions of sub-topics
about popular events
on microblogs
Qingqing Zhou
Department of Information Management, Nanjing University of Science and
Technology, Nanjing, China and Fujian Provincial Key Laboratory of Information
Processing and Intelligent Control, Minjiang University, Fuzhou, China, and
Chengzhi Zhang
Department of Information Management, Nanjing University of Science and
Technology, Nanjing, China, Jiangsu Key Laboratory of Data Engineering and
Knowledge Service, Nanjing University, Nanjing, China and Fujian Provincial
Key Laboratory of Information Processing and Intelligent Control, Minjiang
University, Fuzhou, China
Abstract
Purpose –The development of social media has led to large numbers of internet users now producing
massive amounts of user-generated content (UGC). UGC, which shows users’ opinions about events directly,
is valuable for monitoring public opinion. Current researches have focused on analysing topic evolutions in
UGC. However, few researches pay attention to emotion evolutions of sub-topics about popular events.
Important details about users’ opinions might be missed, as users’ emotions are ignored. This paper aims to
extract sub-topics about a popular event from UGC and investigate the emotion evolutions of each sub-topic.
Design/methodology/approach –This paper rst collects UGC about a popular event as experimental
data and conducts subjectivity classication on the data to get subjective corpus. Second, the subjective
corpus is classied into different emotion categories using supervised emotion classication. Meanwhile, a
topic model is used to extract sub-topics about the event from the subjective corpora. Finally, the authors use
the results of emotion classication and sub-topic extraction to analyze emotion evolutions over time.
Findings –Experimental results show that specic primary emotions exist in each sub-topic and undergo
evolutions differently. Moreover, the authors nd that performance of emotion classier is optimal with term
frequency and relevance frequency as the feature-weighting method.
Originality/value –To the best of the authors’ knowledge, this is the rst research to mine emotion
evolutions of sub-topics about an event with UGC. It mines users’ opinions about sub-topics of event, which
may offer more details that are useful for analysing users’ emotions in preparation for decision-making.
Keywords Correlation analysis, Emotion classication, Emotion evolution, Microblog mining,
Sub-topic evolution, Sub-topic extraction
Paper type Research paper
Introduction
Web 2.0 promotes the rapid development of social media. In 2015, Digital, Social & Mobile
Worldwide (http://wearesocial.net/tag/sdmw/) reported that the number of active social
This work was supported in part by Major Projects of the National Social Science Fund (13&ZD174), the
Fundamental Research Funds for the Central Universities (No.30915011323), Opening Foundation of
Fujian Provincial Key Laboratory of Information Processing and Intelligent Control (Minjiang
University) (No. MJUKF201704).
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EL
35,4
770
Received 21 September 2016
Revised 19 April 2017
Accepted 20 April 2017
TheElectronic Library
Vol.35 No. 4, 2017
pp.770-782
©Emerald Publishing Limited
0264-0473
DOI 10.1108/EL-09-2016-0184
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