基于微信公众号文章的失真健康信息识别方法比较与优化

doi:10.3772/j.issn.1000-0135.2023.02.001

情报学报

2023, Vol. 42

Issue (2): 127-135 DOI: 10.3772/j.issn.1000-0135.2023.02.001

情报理论与方法

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基于微信公众号文章的失真健康信息识别方法比较与优化

王雷¹, 宋士杰², 朱庆华¹

1.南京大学信息管理学院，南京 210023
2.河海大学商学院，南京 211000

Comparison and Improvement of Health Misinformation Identification Methods in WeChat Official Account Articles

Wang Lei¹, Song Shijie², Zhu Qinghua¹

1.School of Information Management, Nanjing University, Nanjing 210023
2.Business School, Hohai University, Nanjing 211000

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摘要近年来，大量失真健康信息以微信公众号文章的方式在社交平台上广为传播，严重影响了用户对健康知识的获取和利用健康信息做医疗决策的效果。为了抑制失真健康信息的传播，有必要对失真健康信息进行自动化的识别与检测。本文以科普中国、丁香医生等公众号发布的健康类文章和经过辟谣的健康类文章为样本，通过分词、去停用词、语法特征提取和文本分类等步骤对失真健康信息进行识别，并通过分类准确率、精确率、召回率、训练时间等性能指标选出效果最佳的分类器。另外，针对文本分类中“一词多义”和“多词一义”的问题，本文通过LDA（latent Dirichlet allocation）主题分析提取文本的语义特征，进而提出一种“语法+语义”的特征提取方法，经过实验验证，各性能指标比基于语义的特征提取方法以及以往相关模型都有了一定的提升。本文为微信公众号文章中失真健康信息的识别提出了一种新的方法和工具，有利于对失真健康信息开展进一步的监测和治理。

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	王雷
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关键词 ：失真健康信息, 语法特征, 语义特征, LDA主题分析, 算法评价, 算法改进

收稿日期: 2021-12-23

基金资助:国家自然科学基金项目“社交媒体环境下失真健康信息的传播机制与协同治理研究”（72174083）；中央高校基本科研业务费人文社科专项“基于消费者视角的社交媒体虚假健康信息纠偏干预研究”（B220201054）。

作者简介: 王雷，男，1995年生，博士研究生，主要研究方向为健康信息学，E-mail：dg20140027@smail.nju.edu.cn；宋士杰，男，1989年生，博士，青年副教授，主要研究方向为健康信息学与信息系统；朱庆华，男，1963年生，教授，博士生导师，主要研究方向为健康信息学与用户信息行为；

引用本文:

王雷, 宋士杰, 朱庆华. 基于微信公众号文章的失真健康信息识别方法比较与优化[J]. 情报学报, 2023, 42(2): 127-135.
Wang Lei, Song Shijie, Zhu Qinghua. Comparison and Improvement of Health Misinformation Identification Methods in WeChat Official Account Articles. 情报学报, 2023, 42(2): 127-135.

链接本文:

https://qbxb.istic.ac.cn/CN/10.3772/j.issn.1000-0135.2023.02.001 或 https://qbxb.istic.ac.cn/CN/Y2023/V42/I2/127

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