2021 Fiscal Year Final Research Report
A Research on High Reliability and Navigation of Health-related Social Media Data
| Project/Area Number |
19K20279
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| Research Category |
Grant-in-Aid for Early-Career Scientists
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| Allocation Type | Multi-year Fund |
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| Review Section |
Basic Section 60080:Database-related
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| Research Institution | Nara Institute of Science and Technology |
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Principal Investigator |
Wakamiya Shoko 奈良先端科学技術大学院大学, 先端科学技術研究科, 准教授 (60727220)
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| Project Period (FY) |
2019-04-01 – 2022-03-31
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| Keywords | ソーシャルメディア / 健康ビッグデータ / ソーシャル・コンピューティング |
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| Outline of Final Research Achievements |
In this project, we attempted to analyze social media data such as tweets on Twitter, extract reliable health big data, and visualize the data by considering diseases and users with the aim of realizing information navigation that provides action guidelines. Specifically, to extract reliable health big data, we examined approaches that use multiple media to supplement missing data and a social reporting application. We also developed social bot and fake news detection techniques for extracting reliable social sensor and content. In addition, taking the COVID-19 pandemic as a case study, we analyzed and visualized information from social media data and web search query data.
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| Free Research Field |
ソーシャルコンピューティング
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| Academic Significance and Societal Importance of the Research Achievements |
ソーシャルメディアには，大量のユーザ生成コンテンツが共有・蓄積されており，健康分野における応用に向けた期待は高まっている．ソーシャルメディアデータを健康ビッグデータとして効果的に活用するために，信頼性の高いユーザやコンテンツの解析だけでなく，得られた結果をどのように可視化し，行動させるかについてまでを含めて，実用化レベルでの健康分野への応用を検討した点で学術的意義や社会的意義があると考えている．
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