SocialGrid: A TCN-enhanced Method for Online Discussion Forecasting
@article{Ling2020SocialGridAT, title={SocialGrid: A TCN-enhanced Method for Online Discussion Forecasting}, author={Chen Ling and R. Wang and Guangmo Tong}, journal={ArXiv}, year={2020}, volume={abs/2003.07189} }
As a means of modern communication tools, online discussion forums have become an increasingly popular platform that allows asynchronous online interactions. People share thoughts and opinions through posting threads and replies, which form a unique communication structure between main threads and associated replies. It is significant to understand the information diffusion pattern under such a communication structure, where an essential task is to predict the arrival time of future events. In… CONTINUE READING
Supplemental Code
Figures, Tables, and Topics from this paper
References
SHOWING 1-10 OF 35 REFERENCES
TiDeH: Time-Dependent Hawkes Process for Predicting Retweet Dynamics
- Computer Science, Physics
- ICWSM
- 2016
- 93
- PDF
A Latent Hawkes Process Model for Event Clustering and Temporal Dynamics Learning with Applications in GitHub
- Computer Science
- 2019 IEEE 39th International Conference on Distributed Computing Systems (ICDCS)
- 2019
- 2
SEISMIC: A Self-Exciting Point Process Model for Predicting Tweet Popularity
- Computer Science, Physics
- KDD
- 2015
- 363
- PDF
Modelling structure and predicting dynamics of discussion threads in online boards
- Computer Science, Mathematics
- J. Complex Networks
- 2019
- 14
- PDF
Personalized Thread Recommendation for MOOC Discussion Forums
- Computer Science, Mathematics
- ECML/PKDD
- 2018
- 12
- Highly Influential
- PDF
Learning online discussion structures by conditional random fields
- Computer Science
- SIGIR '11
- 2011
- 70
- PDF
Modeling and Predicting Popularity Dynamics of Microblogs using Self-Excited Hawkes Processes
- Computer Science
- WWW
- 2015
- 53
- Highly Influential
- PDF