Innovation is fundamental for development and brings competitive advantage for societies and organisations. It consists in the creation of novel complex protocols, technologies, or ideas, and is rarely the result of individual capabilities. Most often, people combine complementary expertise and perspectives to innovate. In this context, social networks play a key role because the social structure defines how information flows and is exchanged between people in a group. In this research project, we will study how the social network structure affects innovation from a dynamic perspective. We plan to design agent-based network models to simulate human characteristics and social/communication interactions to study the mechanisms regulating innovation. From a fundamental point of view, we also aim to identify whether particular network structures may lead to conformism and suppression of innovation. Real-world data in the form of patents, scientific articles, or equivalent, may be used to test our theories by identifying human innovation in professional collaborative networks in the academic sector. We expect to build knowledge and identify general factors, linked to the social network structure, that can be exploited to create value and boost innovation.