Learning Comment Controversy Prediction in Web Discussions Using Incidentally Supervised Multi-Task CNNs-Reference-Cited by-同舟云学术

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Learning Comment Controversy Prediction in Web Discussions Using Incidentally Supervised Multi-Task CNNs

Published:2018 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 9th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis
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Author:

Rethmeier Nils,Hübner Marc,Hennig Leonhard

Publisher

Association for Computational Linguistics

Cited by 5 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Quantifying controversy from stance, sentiment, offensiveness and sarcasm: a fine-grained controversy intensity measurement framework on a Chinese dataset;World Wide Web;2023-08-09

2. Anticipating the Debate: Predicting Controversy in News with Transformer-based NLP;PROCES LENG NAT;2023

3. A novel method detecting controversial interaction in the multiplex social comment network;Frontiers in Physics;2023-01-06

4. MSSF-GCN: Multi-scale Structural and Semantic Information Fusion Graph Convolutional Network for Controversy Detection;Web Information Systems Engineering – WISE 2021;2021

5. Exploiting Open Data to analyze discussion and controversy in online citizen participation;Information Processing & Management;2020-09

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