Public opinion in Japanese newspaper readers’ posts under the prolonged COVID-19 infection spread 2019-2021: Contents analysis using Latent Dirichlet Allocation

These data are based on free description from readers’ posts on Japanese hardcopy newspaper articles in the public domain. Upon searching for “coronavirus,” we found 412 reader submissions during the April 7, 2020 to May 25, 2020, 521 during January 8, 2021 to March 21, 2021, 458 during the April 25, 2021 to June 6, 2021, and 519 during July 12, 2021 to September 30, 2021. Topics of content were extracted by Latent Dirichlet Allocation, and then calculating the ratio of topic occurrence in each description.

Methods
We conducted document analysis on reader’s posts about newspaper articles in the public domain. Many Japanese newspapers have a section where readers can submit their opinions on any topic. Submissions can be made by mail, fax, or e-mail, and readers are asked to disclose their name, occupation, age, address, and contact information. All or part of these disclosed details are often published in the paper.

本数据集源自公有领域内日本纸质报纸文章配套的读者自由留言。以“冠状病毒”为检索关键词进行筛选后，共获取到四批读者投稿：2020年4月7日至2020年5月25日期间412篇，2021年1月8日至2021年3月21日期间521篇，2021年4月25日至2021年6月6日期间458篇，2021年7月12日至2021年9月30日期间519篇。后续通过潜在狄利克雷分配（Latent Dirichlet Allocation）模型提取文本主题，并计算各主题在单篇留言中的出现占比。

研究方法
本研究针对公有领域报纸文章相关的读者留言开展文档分析。多数日本报纸设有读者可针对任意话题提交观点的专栏，投稿可通过邮寄、传真或电子邮件三种渠道提交，投稿者需披露姓名、职业、年龄、住址及联系方式等个人信息，上述披露信息的全部或部分通常会随留言一同刊载于报纸版面。