Games User Research: Network Analysis

A thriving settlement on one island, a failing one on another. A rumor spreading like wildfire, but who are the influencers? A powerful faction forms, but what holds it together?

In today's complex, multiplayer games, we can see what players do. But to truly understand and shape their experience, we need to see the invisible social fabric that connects them. We need to understand the why. Games User Research: Network Analysis is your definitive hands-on guide to mastering this powerful discipline. Through the lens of the fictional Finnish survival game, "Nordic Pond," and its world-shattering "The New Islands" expansion, this book demystifies the art of network analysis. It transforms it from an academic alchemy into a practical, indispensable tool for every GUR professional, game designer, data analyst, and community manager.

Forget expensive software. This guide champions the use of powerful and accessible Free and Open Source Software (FOSS) like Gephi, alongside data wrangling workhorses like R and Python, to turn raw interaction data into profound, actionable wisdom.

What You Will Learn

This book is structured to take you from foundational theory to advanced, practical application, using the dynamic world of "The New Islands" as a running case study.

• Part I: Foundations of Network Analysis for GUR: Learn to "think in connections" and master the basic vocabulary of graph theory (nodes, edges, attributes). Master the art of data wrangling with R and Python to forge raw player logs into clean, network-ready formats.
• Part II: Visualizing and Analyzing Networks with FOSS: Dive into Gephi to transform chaotic "hairball" graphs into clear, insightful visualizations. Learn to quantify your findings by calculating and interpreting key metrics to find influential players, and use community detection algorithms to uncover emergent social cliques and economic blocs.
• Part III: Applications of Network Analysis in GUR: Apply your skills to core GUR challenges. Conduct Player Social Network Analysis (SNA) to understand community health , use Process Mining to trace the actual "footprints" players leave in your quest and UI flows , and even transform rich qualitative data from player diaries and forums into "networks of meaning".
• Part IV: Advanced Techniques, Case Studies, and Future Horizons: Explore dynamic network analysis to see how communities evolve over time. Delve into using network features for predictive modeling to forecast player churn and chart the unique "odyssey" of individual players. Finally, examine the future of the field with AI and the ethical responsibilities that come with these powerful methods.

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This book is also available as a physical softcover copy. To get yours, please visit: https://indieuxr.fi/GURNA/