Personalized Microblog Sentiment Classification via Multi-Task Learning

  title={Personalized Microblog Sentiment Classification via Multi-Task Learning},
  author={Fangzhao Wu and Yongfeng Huang},
Microblog sentiment classification is an interesting and important research topic with wide applications. Traditional microblog sentiment classification methods usually use a single model to classify the messages from different users and omit individuality. However, microblogging users frequently embed their personal character, opinion bias and language habits into their messages, and the same word may convey different sentiments in messages posted by different users. In this paper, we propose… CONTINUE READING


Publications citing this paper.
Showing 1-10 of 10 extracted citations

Towards Personalized Learning in Mobile Sensing Systems

2018 IEEE 38th International Conference on Distributed Computing Systems (ICDCS) • 2018
View 1 Excerpt


Publications referenced by this paper.
Showing 1-10 of 27 references

Proximal algorithms

N. Parikh, S. Boyd
Foundations and Trends in Optimization 1(3):123–231. • 2013
View 4 Excerpts
Highly Influenced

Distributed optimization and statistical learning via the alternating direction method of multipliers

S. Boyd, N. Parikh, E. Chu, B. Peleato, J. Eckstein
Foundations and Trends R • 2011
View 6 Excerpts
Highly Influenced

A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems

SIAM J. Imaging Sciences • 2009
View 4 Excerpts
Highly Influenced

Regularized multi--task learning

View 9 Excerpts
Highly Influenced

laborative boosting for activity classification in microblogs

K. Song, S. Feng, +3 authors K.-F. Wong
View 5 Excerpts
Highly Influenced

Collaborative Online Multitask Learning

IEEE Transactions on Knowledge and Data Engineering • 2014
View 1 Excerpt

Similar Papers

Loading similar papers…