Successful New-entry Prediction for Multi-Party Online Conversations via Latent Topics and Discourse Modeling.
Lingzhi Wang|Jing Li|Xingshan Zeng|Kam-Fai Wong
| Anthology ID: | DBLP:conf/www/WangLZW22 |
|---|---|
| Volume: | WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25 - 29, 2022 |
| Year: | 2022 |
| Venue: | The Web Conference (WWW) |
| Publisher: | ACM |
| Pages: | 1663-1672 |
| URL: | https://doi.org/10.1145/3485447.3512285 |
| DOI: | https://doi.org/10.1145/3485447.3512285 |
| DBLP: | conf/www/WangLZW22 |
| BibTeX: |
@inproceedings{wang-2022-successful,
author = {Lingzhi Wang and
Jing Li and
Xingshan Zeng and
Kam-Fai Wong},
editor = {Fr\'{e}d\'{e}rique Laforest and
Rapha\"{e}l Troncy and
Elena Simperl and
Deepak Agarwal and
Aristides Gionis and
Ivan Herman and
Lionel M\'{e}dini},
title = {{Successful New-entry Prediction for Multi-Party Online Conversations via Latent Topics and Discourse Modeling}},
booktitle = {{WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25 - 29, 2022}},
pages = {1663--1672},
publisher = {ACM},
year = {2022},
url = {https://doi.org/10.1145/3485447.3512285},
doi = {https://doi.org/10.1145/3485447.3512285}
}