Fundamental Technologies for Information Sharing and Behavior Change Actuation in SNSs
| Project/Area Number |
18H03339
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Review Section |
Basic Section 62020:Web informatics and service informatics-related
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| Research Institution | The University of Tokyo |
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Principal Investigator |
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| Project Period (FY) |
2018-04-01 – 2021-03-31
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| Project Status |
Completed (Fiscal Year 2020)
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| Budget Amount *help |
¥17,160,000 (Direct Cost: ¥13,200,000、Indirect Cost: ¥3,960,000)
Fiscal Year 2020: ¥5,720,000 (Direct Cost: ¥4,400,000、Indirect Cost: ¥1,320,000)
Fiscal Year 2019: ¥5,720,000 (Direct Cost: ¥4,400,000、Indirect Cost: ¥1,320,000)
Fiscal Year 2018: ¥5,720,000 (Direct Cost: ¥4,400,000、Indirect Cost: ¥1,320,000)
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| Keywords | マルチメディア / SNS / 情報発信 / 魅力工学 / 情報共有 / 行動変容 |
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| Outline of Final Research Achievements |
In this project, we analyzed why and how users get attracted to some content in SNSs. Namely, we tried to analyze, tell reasons, and even enhance such “attractiveness” in multimedia big data by using deep learning technologies.
We also extend our work on SNS analysis to other areas such as presentation and communication, online advertisement, product package design, apartment recommendation, and so on by collaborating with industry. As a result, we succeeded in publishing a lot of research works that are also useful for industrial applications.
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| Academic Significance and Societal Importance of the Research Achievements |
SNSでの人気度を考慮したハッシュタグ推薦や画像編集の研究は世界的に見ても独自性が高い。研究成果の中にはACM MultimediaやAAAIに採択されたものもあり、学術的に意義のある研究を実施できた。
また、研究成果の概要にも述べた通り、産業分野に応用可能な研究に発展させることができたものもある。企業との共同研究やライセンス提供に至り、実サービスの中で実用性が確認できたものも少なくない。例えばプレゼンの解析技術については日経新聞で報道されたほか、商品パッケージの印象予測も我々の技術を用いることで商品の売上が1.3倍となったことが報道され話題となるなど、社会的インパクトを与えた。
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Report
(4 results)
Research Products
(65 results)
