# Constructing Vec-tionaries to Extract Message Features from Texts: A Case Study of Moral Appeals

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/constructing-vec-tionaries-to-extract-message-features-from-texts-a-case-study/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Zening Duan,Anqi Shao,Yi-Cheng Hu,H. Y. Lee,Xining Liao,Yoo Ji Suh,Ji‐Soo Kim,Kaicheng Yang,Kaiping Chen,Sijia Yang |
| Citations | 0 |
| DOI | 10.48550/arxiv.2312.05990 |
| Fields | Computer Science,Social Sciences |
| Open Access | true |
| OA Status | green |
| OA URL | https://arxiv.org/pdf/2312.05990 |
| OpenAlex ID | https://openalex.org/W4389650849 |
| Type | preprint |
| Year | 2023 |

## Paper authors

- [Yoo Ji Suh](https://scholariq.org/researchers/yoo-ji-suh/)

## Paper journal

- [arXiv (Cornell University)](https://scholariq.org/journals/arxiv-cornell-university/)

## Paper primary topic

- [Hate Speech and Cyberbullying Detection](https://scholariq.org/topics/hate-speech-and-cyberbullying-detection/)

## Paper topics

- [Hate Speech and Cyberbullying Detection](https://scholariq.org/topics/hate-speech-and-cyberbullying-detection/)
- [Sentiment Analysis and Opinion Mining](https://scholariq.org/topics/sentiment-analysis-and-opinion-mining/)
- [Social Media and Politics](https://scholariq.org/topics/social-media-and-politics/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.