Jurnal SINTA 2
Opinion Mining for User Generated Design by Social Networking Service and Japanese Manga
Journal of ICT Research and Applications (JICTRA) · Vol. 5 No. 3 (2013) · pp. 223–240
- ISSN
- 2338-5499, 2337-5787
- Published
- 2013-09-13
- Publisher
- DRI - ITB
- Language
- eng
Abstract
The growth of Social Networking Service (SNS) has created a new potential in marketing. While users communicate and interact via SNS, the list of their conversation, which is called casual data can be used to determine their needs or aspirations. SNS can be very useful for product/service developers, especially when developing new ideas or simply evaluating the feasibility of their existing products/services. Furthermore, SNS provides a unique system that enables expressive and two-way communication between its users. SNS is known for its effectiveness in delivering fresh news and information, thus it can be used as promotional media. Although several online services that utilize SNS and casual data have been provided, the purpose of those services is still unclear and ineffective. In those services, users were only asked for their opinions without receiving sufficient feedbacks. Therefore, to solve these problems we propose an innovative way of utilizing SNS and casual data in designing user generated design. In our proposed system, users can directly contribute to the product/service development process in an interesting way. We designed an online service, which allows users to posts manga that describes their original idea. While contributing to the product/service development, they can also benefit from expressing their hobbies and receiving feedbacks from other users.
Collaboration network of the authors
8 authors · 22 co-authorship links
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- Kyushu University
- Different organisations
- Same organisation
- Affiliation unknown
- Thicker line = more joint articles · bigger circle = more articles
Show as table
| Co-author | Organisation | Joint articles |
|---|---|---|
| Hamdan Gani | Kyushu University | 1 |
Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.