Social Network Analysis

In previous sections, we discussed methods for collecting social media data from platforms like Facebook, Twitter, and internet forums. These data-driven approaches unlock opportunities to gain a deep understanding of users, consumers, and general audiences. Companies can monitor emotions, trending topics, and keywords in user-generated content.

However, to fully extract value, it is crucial to examine the relationships and connections between users and the content they engage with on social media. This is where social network analysis (SNA), a technique rooted in graph theory, becomes invaluable.

This section will introduce techniques for analysing both topic networks and user networks. We will explore these concepts using examples from platforms like Twitter and Pinterest to illustrate the power of SNA in understanding social dynamics.

Social network analysis provides a powerful framework to visualize and understand relationships—whether between users or topics. By applying graph theory, researchers and businesses can decode the underlying structures of social media networks, identifying key influencers, emergent communities, and the flow of information. As our understanding of social networks continues to evolve, SNA will play an increasingly critical role in shaping strategies for navigating the digital landscape.