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公众对疾病的看法:基于新闻媒体数据的信息流行病学研究

Public Opinions Toward Diseases: Infodemiological Study on News Media Data.

作者信息

Huang Ming, ElTayeby Omar, Zolnoori Maryam, Yao Lixia

机构信息

Department of Health Sciences Research, Mayo Clinic, Rochester, MN, United States.

Department of Computer Science, University of North Carolina at Charlotte, Charlotte, NC, United States.

出版信息

J Med Internet Res. 2018 May 8;20(5):e10047. doi: 10.2196/10047.

Abstract

BACKGROUND

Society always has limited resources to expend on health care, or anything else. What are the unmet medical needs? How do we allocate limited resources to maximize the health and welfare of the people? These challenging questions might be re-examined systematically within an infodemiological frame on a much larger scale, leveraging the latest advancement in information technology and data science.

OBJECTIVE

We expanded our previous work by investigating news media data to reveal the coverage of different diseases and medical conditions, together with their sentiments and topics in news articles over three decades. We were motivated to do so since news media plays a significant role in politics and affects the public policy making.

METHODS

We analyzed over 3.5 million archive news articles from Reuters media during the periods of 1996/1997, 2008 and 2016, using summary statistics, sentiment analysis, and topic modeling. Summary statistics illustrated the coverage of various diseases and medical conditions during the last 3 decades. Sentiment analysis and topic modeling helped us automatically detect the sentiments of news articles (ie, positive versus negative) and topics (ie, a series of keywords) associated with each disease over time.

RESULTS

The percentages of news articles mentioning diseases and medical conditions were 0.44%, 0.57% and 0.81% in the three time periods, suggesting that news media or the public has gradually increased its interests in medicine since 1996. Certain diseases such as other malignant neoplasm (34%), other infectious diseases (20%), and influenza (11%) represented the most covered diseases. Two hundred and twenty-six diseases and medical conditions (97.8%) were found to have neutral or negative sentiments in the news articles. Using topic modeling, we identified meaningful topics on these diseases and medical conditions. For instance, the smoking theme appeared in the news articles on other malignant neoplasm only during 1996/1997. The topic phrases HIV and Zika virus were linked to other infectious diseases during 1996/1997 and 2016, respectively.

CONCLUSIONS

The multi-dimensional analysis of news media data allows the discovery of focus, sentiments and topics of news media in terms of diseases and medical conditions. These infodemiological discoveries could shed light on unmet medical needs and research priorities for future and provide guidance for the decision making in public policy.

摘要

背景

社会用于医疗保健或其他任何方面的资源总是有限的。未满足的医疗需求有哪些?我们如何分配有限的资源以最大化民众的健康和福祉?利用信息技术和数据科学的最新进展,这些具有挑战性的问题可能会在一个更大规模的信息流行病学框架内得到系统的重新审视。

目的

我们通过调查新闻媒体数据来扩展之前的工作,以揭示不同疾病和医疗状况在三十年新闻文章中的报道情况,以及它们的情感倾向和主题。我们之所以这样做,是因为新闻媒体在政治中发挥着重要作用,并影响公共政策的制定。

方法

我们使用描述性统计、情感分析和主题建模,分析了路透社媒体在1996/1997年、2008年和2016年期间的350多万篇存档新闻文章。描述性统计说明了过去三十年各种疾病和医疗状况的报道情况。情感分析和主题建模帮助我们自动检测新闻文章的情感倾向(即正面与负面)以及随时间与每种疾病相关的主题(即一系列关键词)。

结果

在这三个时间段内,提及疾病和医疗状况的新闻文章百分比分别为0.44%、0.57%和0.81%,这表明自1996年以来,新闻媒体或公众对医学的兴趣逐渐增加。某些疾病,如其他恶性肿瘤(34%)、其他传染病(20%)和流感(11%)是报道最多的疾病。在新闻文章中,发现226种疾病和医疗状况(97.8%)具有中性或负面情感倾向。通过主题建模,我们确定了这些疾病和医疗状况的有意义主题。例如,吸烟主题仅在1996/1997年出现在关于其他恶性肿瘤的新闻文章中。主题短语“HIV”和“寨卡病毒”分别在1996/1997年和2016年与其他传染病相关联。

结论

对新闻媒体数据的多维度分析能够发现新闻媒体在疾病和医疗状况方面的关注点、情感倾向和主题。这些信息流行病学发现可以揭示未满足的医疗需求和未来的研究重点,并为公共政策决策提供指导。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8370/5964307/aa3f622c706c/jmir_v20i5e10047_fig1.jpg

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