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报纸上关于三手烟文章的数据分析与可视化:一种主题建模方法

Data Analysis and Visualization of Newspaper Articles on Thirdhand Smoke: A Topic Modeling Approach.

作者信息

Liu Qian, Chen Qiuyi, Shen Jiayi, Wu Huailiang, Sun Yimeng, Ming Wai-Kit

机构信息

School of Journalism and Communication, Jinan University, Guangzhou, China.

National Media Experimental Teaching Demonstration Center, Jinan University, Guangzhou, China.

出版信息

JMIR Med Inform. 2019 Jan 29;7(1):e12414. doi: 10.2196/12414.

DOI:10.2196/12414
PMID:30694199
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6371067/
Abstract

BACKGROUND

Thirdhand smoke has been a growing topic for years in China. Thirdhand smoke (THS) consists of residual tobacco smoke pollutants that remain on surfaces and in dust. These pollutants are re-emitted as a gas or react with oxidants and other compounds in the environment to yield secondary pollutants.

OBJECTIVE

Collecting media reports on THS from major media outlets and analyzing this subject using topic modeling can facilitate a better understanding of the role that the media plays in communicating this health issue to the public.

METHODS

The data were retrieved from the Wiser and Factiva news databases. A preliminary investigation focused on articles dated between January 1, 2013, and December 31, 2017. Use of Latent Dirichlet Allocation yielded the top 10 topics about THS. The use of the modified LDAvis tool enabled an overall view of the topic model, which visualizes different topics as circles. Multidimensional scaling was used to represent the intertopic distances on a two-dimensional plane.

RESULTS

We found 745 articles dated between January 1, 2013, and December 31, 2017. The United States ranked first in terms of publications (152 articles on THS from 2013-2017). We found 279 news reports about THS from the Chinese media over the same period and 363 news reports from the United States. Given our analysis of the percentage of news related to THS in China, Topic 1 (Cancer) was the most popular among the topics and was mentioned in 31.9% of all news stories. Topic 2 (Control of quitting smoking) was related to roughly 15% of news items on THS.

CONCLUSIONS

Data analysis and the visualization of news articles can generate useful information. Our study shows that topic modeling can offer insights into understanding news reports related to THS. This analysis of media trends indicated that related diseases, air and particulate matter (PM), and control and restrictions are the major concerns of the Chinese media reporting on THS. The Chinese press still needs to consider fuller reports on THS based on scientific evidence and with less focus on sensational headlines. We recommend that additional studies be conducted related to sentiment analysis of news data to verify and measure the influence of THS-related topics.

摘要

背景

多年来,三手烟在中国一直是一个日益受到关注的话题。三手烟(THS)由残留在表面和灰尘中的烟草烟雾污染物组成。这些污染物会重新释放为气体,或与环境中的氧化剂及其他化合物发生反应,产生二次污染物。

目的

收集各大媒体关于三手烟的报道,并使用主题建模对这一主题进行分析,有助于更好地理解媒体在向公众传播这一健康问题中所起的作用。

方法

数据从Wiser和Factiva新闻数据库中检索。初步调查聚焦于2013年1月1日至2017年12月31日期间的文章。使用潜在狄利克雷分配算法得出了关于三手烟的前10大主题。使用改进后的LDAvis工具可以全面了解主题模型,该工具将不同主题可视化为圆圈。多维缩放用于在二维平面上表示主题间的距离。

结果

我们发现了2013年1月1日至2017年12月31日期间的745篇文章。就出版物数量而言,美国排名第一(2013 - 2017年有152篇关于三手烟的文章)。同期我们发现中国媒体有279篇关于三手烟的新闻报道,美国有363篇新闻报道。根据我们对中国与三手烟相关新闻所占百分比的分析,主题1(癌症)在所有主题中最受欢迎,在所有新闻报道中被提及的比例为31.9%。主题2(戒烟控制)约占三手烟新闻报道的15%。

结论

新闻文章的数据分析和可视化可以产生有用的信息。我们的研究表明,主题建模能够为理解与三手烟相关新闻报道提供见解。对媒体趋势的这一分析表明,相关疾病、空气和颗粒物(PM)以及控制与限制是中国媒体报道三手烟时的主要关注点。中国媒体仍需基于科学证据,减少对耸人听闻标题的关注,并考虑对三手烟进行更全面的报道。我们建议开展更多与新闻数据情感分析相关的研究,以验证和衡量与三手烟相关主题的影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d7d/6371067/f73b47ece227/medinform_v7i1e12414_fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d7d/6371067/59b4e59918e8/medinform_v7i1e12414_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d7d/6371067/5ddb78c2cf5f/medinform_v7i1e12414_fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d7d/6371067/8aa177d83956/medinform_v7i1e12414_fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d7d/6371067/f73b47ece227/medinform_v7i1e12414_fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d7d/6371067/59b4e59918e8/medinform_v7i1e12414_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d7d/6371067/5ddb78c2cf5f/medinform_v7i1e12414_fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d7d/6371067/8aa177d83956/medinform_v7i1e12414_fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d7d/6371067/f73b47ece227/medinform_v7i1e12414_fig4.jpg

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