Creating social intelligence for product portfolio design

• User-generated data sources have been utilized promisingly for product creation.
• The intelligence mechanism can consolidate the reviews expressed in social media.
• Analyzing the reviewers' knowledge, authority, and sentiment on the products
• Deriving feature specification and feature importance for next-generation products
• The proposed mechanism enhances market trend prediction and customer acceptance.

Increasing numbers of people are using social media to express their personal experiences. Recently, these plentiful user-generated data sources have been utilized promisingly by enterprises for product creation. In this research, we propose a social intelligence mechanism that can extract and consolidate the reviews expressed via social media and derive insights (product feature specification and feature importance) to help enterprises make decisions on developing next-generation products by analyzing the reviewers' knowledge and authority and their opinion sentiment toward the target products. The experimental results obtained using Epinions.com show that the proposed mechanism outperforms other benchmark approaches in market trend prediction and customer acceptance.