Abstract
This study analyzes users' needs based on questions and the adequacy and quality of content in responses from participants in the ZHIHU Q&A online community (the largest Q&A platform in China). It aims to provide a basis for improving the management of online Q&A systems and enhancement of depression literacy for platform users. Python was used to crawl the question and response records found on depression in the ZHIHU, and the hot question records were classified by k-means clustering. The top 100 hot question records were then selected, and this research manually marked the answers with more than 40 likes for each question based on five dimensions of objectivity, integrity, professionalism, persuasiveness and practicality. The query content contained 685 hot questions. The results of cluster analysis showed that the questions about depression could be divided into four categories: basic knowledge, social life, self-management/prevention and education. In the annotated answers, the frequency of responses of higher quality of objectivity, persuasiveness and practicality was 89.81%, 65.64% and 73.24%, respectively, while the proportion of those regarding higher quality of professionalism and integrity was 33.21% and 16.79%. Users were found to have a high rate of demand for depression health information, but most of the responses on depression in the ZHIHU community were low-level and inadequate. Professionals and qualified volunteers should be encouraged to provide standardized answers to popular questions and contribute to a high-quality Q&A system. More rigorous management of the ZHIHU community should be designed to provide a high quality educational resource for platform users.
| Original language | English |
|---|---|
| Title of host publication | ISAIMS '21 |
| Subtitle of host publication | Proceedings of the 2nd International Symposium on Artificial Intelligence for Medicine Sciences |
| Publisher | Association for Computing Machinery |
| Pages | 551-556 |
| Number of pages | 6 |
| ISBN (Electronic) | 9781450395588 |
| DOIs | |
| Publication status | Published - Oct 2021 |
| Event | 2nd International Symposium on Artificial Intelligence for Medicine Sciences, ISAIMS 2021 - Virtual, Online, China Duration: 29 Oct 2021 → 31 Oct 2021 |
Publication series
| Name | ACM International Conference Proceeding Series |
|---|
Conference
| Conference | 2nd International Symposium on Artificial Intelligence for Medicine Sciences, ISAIMS 2021 |
|---|---|
| Country/Territory | China |
| City | Virtual, Online |
| Period | 29/10/21 → 31/10/21 |
Bibliographical note
Publisher Copyright:© 2021 ACM.
Funding
We would like to thank Professor Yang Bingxiang for her careful guidance in the writing of this article. Funding:This study is supported by the National Natural Science Foundation of China (No. 72174152), Wuhan university provincial college students' innovation and entrepreneurship training program (W2020305004) and Wuhan university 2019 school of medicine students' innovation and entrepreneurship training program (MS2019050).
| Funders | Funder number |
|---|---|
| Wuhan university provincial college students' innovation and entrepreneurship training program | W2020305004, MS2019050 |
| National Natural Science Foundation of China | 72174152 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 4 Quality Education
Keywords
- Answer quality analysis
- Depression
- depression information needs
- Q&A community
- ZHIHU
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