|Title:||Hashtags, emotions, and comments : a large-scale dataset to understand fine-grained social emotions to online topics|
|Advisors:||Li, Jing Amelia (COMP)|
|Subject:||Online social networks -- Psychological aspects|
Hong Kong Polytechnic University -- Dissertations
|Department:||Department of Computing|
|Pages:||x, 46 pages : color illustrations|
|Abstract:||This paper studies social emotions to online discussion topics. While most prior work focus on emotions from writers, we investigate readers' responses and explore the public feelings to an online topic. A large-scale dataset is collected from Chinese microblog Sina Weibo with over 13 thousand trending topics, emotion votes in 24 fine-grained types from massive participants, and user comments to allow context understanding. In experiments, we examine baseline performance to predict a topic's possible social emotions in a multi-label classification setting. The results show that a seq2seq model with user comment modeling performs the best, even surpassing human prediction. More analyses shed light on the effects of emotion types, topic description lengths, contexts from user comments and the limited capacity of the existing models.|
|Rights:||All rights reserved|
Files in This Item:
|5817.pdf||For All Users (off-campus access for PolyU Staff & Students only)||1.81 MB||Adobe PDF||View/Open|
As a bona fide Library user, I declare that:
- I will abide by the rules and legal ordinances governing copyright regarding the use of the Database.
- I will use the Database for the purpose of my research or private study only and not for circulation or further reproduction or any other purpose.
- I agree to indemnify and hold the University harmless from and against any loss, damage, cost, liability or expenses arising from copyright infringement or unauthorized usage.
By downloading any item(s) listed above, you acknowledge that you have read and understood the copyright undertaking as stated above, and agree to be bound by all of its terms.
Please use this identifier to cite or link to this item: