2014 IEEE Computers, Communications and IT Applications Conference 2014
DOI: 10.1109/comcomap.2014.7017205
|View full text |Cite
|
Sign up to set email alerts
|

Sentiment analysis on Weibo data

Abstract: With the development of the Internet, people share their emotion statuses or attitudes on online social websites, leading to an explosive rise on the scale of data. Mining sentiment information behind these data helps people know about public opinions and social trends. In this paper a sentiment analysis algorithm adapting to Weibo (Microblog) data is proposed. Given that a Weibo post is usually short, LDA model is used to generate text features based on semantic information instead of text structure. To decid… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Year Published

2019
2019
2023
2023

Publication Types

Select...
2

Relationship

0
2

Authors

Journals

citations
Cited by 2 publications
(1 citation statement)
references
References 14 publications
0
1
0
Order By: Relevance
“…Social media has made it possible for millions of people to share their emotions and attitudes on online social networks, leading to an explosion in the volume of relevant data. Using sentiment analysis to examine these data allows researchers to learn about public attitudes and social trends (Di et al, 2014).…”
Section: Sentiment Analysismentioning
confidence: 99%
“…Social media has made it possible for millions of people to share their emotions and attitudes on online social networks, leading to an explosion in the volume of relevant data. Using sentiment analysis to examine these data allows researchers to learn about public attitudes and social trends (Di et al, 2014).…”
Section: Sentiment Analysismentioning
confidence: 99%