Summary of The Role Of Emotions in Informational Support Question-response Pairs in Online Health Communities: a Multimodal Deep Learning Approach, by Mohsen Jozani and Jason A. Williams and Ahmed Aleroud and Sarbottam Bhagat
The Role of Emotions in Informational Support Question-Response Pairs in Online Health Communities: A Multimodal Deep Learning Approach
by Mohsen Jozani, Jason A. Williams, Ahmed Aleroud, Sarbottam Bhagat
First submitted to arxiv on: 21 May 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Social and Information Networks (cs.SI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The proposed study investigates the correlation between question types, response contents, and helpfulness ratings in online health communities. To achieve this, the authors created a labeled dataset of question-response pairs and designed multimodal machine learning models to accurately predict informational support questions and responses. Additionally, they employed explainable AI techniques to uncover the emotions embedded in these exchanges, highlighting the significance of emotional intelligence in providing informational support. This research fills a gap in understanding the complex interplay between emotional and informational support. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This study looks at how people ask for help and get answers online when discussing health issues. The researchers made a special dataset with questions and answers and used computer programs to learn from it. They also figured out how to understand what emotions are behind these conversations, showing that emotions matter when giving helpful advice. This is important research that helps us better understand how people support each other online. |
Keywords
» Artificial intelligence » Machine learning
