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Social Graph

Summary

The Social Graph represents the network of relationships between people on social media platforms and digital channels. It captures who is connected to whom through friendships, follows, mentions, and interactions. Understanding the social graph helps organizations identify influencers, understand information flow, and leverage network effects for marketing and customer engagement.

The Challenge

Organizations attempting to leverage social media face significant obstacles:

  • Platform fragmentation — Customers maintain different social networks across multiple platforms (LinkedIn, Twitter/X, Facebook, Instagram, TikTok)
  • Privacy restrictions — Platform APIs increasingly restrict access to social graph data
  • Scale and velocity — Billions of users creating and changing connections in real-time
  • Multiple relationship types — Friends, followers, subscribers, connections each mean different things
  • Bot detection — Distinguishing genuine social connections from automated bot networks
  • Cross-platform identity — Linking the same person's accounts across different platforms
  • Network evolution — Social connections constantly form and dissolve

Traditional analytics tools treat social media as isolated data sources, missing the interconnected nature of social networks.

Why EKG is Required

Enterprise Knowledge Graphs are ideally suited for social graph analysis:

  • Native graph structure — Social networks are literally graphs; EKG provides natural representation
  • Multi-platform integration — Unify social connections across LinkedIn, Twitter, Facebook, and proprietary platforms
  • Identity resolution — Link the same individual across different social media accounts
  • Network analysis — Calculate centrality, influence, community structure using graph algorithms
  • Real-time updates — Continuously update the social graph as new connections form
  • Cross-domain linking — Connect social media identities to customer records, transactions, and interactions
  • Privacy-preserving aggregation — Analyze network patterns while respecting individual privacy

Business Value

  • Influencer identification — Find customers with large, engaged networks for brand advocacy programs
  • Viral marketing — Understand network structure to optimize campaign seeding and information spread
  • Customer acquisition — Leverage social connections for lookalike targeting and referral programs
  • Brand monitoring — Track how brand mentions and sentiment spread through social networks
  • Risk detection — Identify coordinated inauthentic behavior, bot networks, and manipulation campaigns
  • Community insights — Understand customer communities and subcultures for product development
  • Network effects — Optimize products and features that benefit from network effects

Comparison with Interest Graph

The Social Graph focuses on who knows whom — the relationships between people. The Interest Graph focuses on what people care about — the relationships between people and topics, brands, and content. Both are complementary views that together provide a complete picture of social media dynamics.