Advancing Stance Detection of Political Fan Pages: A Multimodal Approach-Reference-Cited by-同舟云学术

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Advancing Stance Detection of Political Fan Pages: A Multimodal Approach

Published:2024-05-13 Issue: Volume: Page:702-705
ISSN:
Container-title:Companion Proceedings of the ACM Web Conference 2024
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Author:

Kuo Kuan-Hung¹^ORCID,Wang Ming-Hung¹^ORCID,Kao Hung-Yu²^ORCID,Dai Yu-Chen³^ORCID

Affiliation:

1. Department of Computer Science and Information Engineering, National Chung Cheng University, Chiayi, Taiwan

2. Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan

3. National Institute of Cyber Security, Tainan, Taiwan

Funder

National Science and Technology Council

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3589335.3651467

Reference21 articles.

1. Incorporating Hand-crafted Features in a Neural Network Model for Stance Detection on Microblog

2. A novel approach to stance detection in social media tweets by fusing ranked lists and sentiments

3. Hangbo Bao Li Dong Songhao Piao and Furu Wei. 2022. BEiT: BERT Pre-Training of Image Transformers. arxiv: 2106.08254 [cs.CV]

4. Wei-Fan Chen and Lun-Wei Ku. 2016. UTCNN: a Deep Learning Model of Stance Classificationon on Social Media Text. arxiv: 1611.03599 [cs.CL]

5. Unsupervised User Stance Detection on Twitter

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