Social network structure-based framework for innovation evaluation and propagation for new product development
- Publisher:
- Springer Science and Business Media LLC
- Publication Type:
- Journal Article
- Citation:
- Service Oriented Computing and Applications, 2020, 14, (3), pp. 189-201
- Issue Date:
- 2020-09-01
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| Filename | Description | Size | |||
|---|---|---|---|---|---|
| Akbari2020_Article_SocialNetworkStructure-basedFr.pdf | 3.03 MB |
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© 2020, Springer-Verlag London Ltd., part of Springer Nature. Evaluating the innovation of a new idea before its implementation is a complicated but important phenomenon as it plays a critical role in the success of a product. The literature widely uses sentiment analysis as a technique for product designers to ascertain users’ opinion toward an idea before its implementation. However, that technique focuses only on determining the opinion of users studied. It does not assist designers in providing insights in terms of what needs to be done to propagate the popularity of the idea further to ensure its success. One framework by which this can be done is by considering social network structure and representing users as nodes of that network. In this paper, we investigate how a social network structure can be used to influence a user’s opinion among the society. Our proposed framework consists of four main components, namely data collection, sentiment extraction, budget approximation and presentation. After gathering customers’ comments in the data collection phase, the opinion of users who have expressed it is analyzed in the sentiment analysis phase. The budget approximation component then determines the cost of spreading positive opinion among the network of users, including those who have not given it. For that, influence maximization is used to compare the cost of convergence of the general opinion of society in the direction of innovation. In presentation component, the comparative information will be used by product designers to assist them in determining the viability of selecting an idea for implementation. The simulation results show that the network structure and the individuals’ positions are important factors in the acceptance of an innovation by society. This framework can be used to compare different innovative ideas and provide decision makers in organizations with informative reports as decision support materials.
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