Abstract
The increasing popularity of online two-sided market has led to the growth of user-generated content such as customer reviews and social links. This user-generated content can be analyzed to increase both the stand-alone value of products (services) and to expand the network effects in two-sided markets. For this purpose, this study attempts to analyze the user-generated content in two-sided markets to provide recommendations on products (services) and social links. Design science is used as the research method. Social proof theory and homophily theory serve as the theoretical bases to guide the research design. Drawing upon these two theories, the design principles and the recommender system prototype for two-sided markets are proposed by combining social network analysis and sentiment analysis.
| Original language | English |
|---|---|
| Title of host publication | Amcis 2015 Proceedings |
| Number of pages | 11 |
| State | Published - 2015 |
Keywords
- Two-sided market
- Design science
- Recommender system
- Sentiment analysis
- Social network analysis