中文在线医疗社区问答文本数据集-29576

数据集获取（Figshare）

• 源站标题：Q&A TEXT IN A CHINESE ONLINE MEDICAL COMMUNITY
• DOI：10.6084/m9.figshare.21972626.v1
• 发布日期：2023-01-29
• 文件数：1 个
• 文件总体积：21.82 MB
• 源站页面：https://figshare.com/articles/dataset/Q_A_TEXT_IN_A_CHINESE_ONLINE_MEDICAL_COMMUNITY/21972626

命令行下载

curl -L -o "ori_data_final.csv" "https://ndownloader.figshare.com/files/38985167"

文件清单

• ori_data_final.csv（21.82 MB）

文件总体积 21.82 MB（源站 API 实测）。

数据加载示例（表格/文本类）

import pandas as pd, glob, os

files = (glob.glob(os.path.join(path, "**", "*.csv"), recursive=True)
       + glob.glob(os.path.join(path, "**", "*.tsv"), recursive=True)
       + glob.glob(os.path.join(path, "**", "*.xlsx"), recursive=True))
print("数据文件:", files)
df = pd.read_csv(files[0])
print(df.shape); print(df.columns.tolist()); print(df.head(3))

数据说明

Using Python. we crawl a total of 18, 793 diabetes related Q&A between Jun. 1, 2016 and Sept. 1, 2020 on xywy.com, a famous Chinese Online Medical Community. Each data contains four parts of the question detail page: Title, Problem Description, User ID and Question Time, and three parts of the doctor’s answer page: Doctor ID, Answer Content and Answer Time. After preprocessing such as cleaning and deduplication, we finally obtain 18,521 valid data. Considering the Problem Description contains the background information of the doctor’s answer, we combine the two into the Answer Content, which is used as the text of the knowledge graph construction later.

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.6084/m9.figshare.21972626.v1（source: https://figshare.com/articles/dataset/Q_A_TEXT_IN_A_CHINESE_ONLINE_MEDICAL_COMMUNITY/21972626）。