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Granular Age Prediction Analysis in Online Gaming: Insights from Player Data

This report presents a comprehensive analysis of age prediction for players in an online gaming environment. We break down player data into specific age groups and explore various factors such as player level, race, gender, class, guild rank, education, employment status, and gaming experience. Using data extracted from the Nagafen server, we employ model building techniques to enhance our understanding of player demographics and behavior. The findings will contribute to improving player engagement strategies and tailored game experiences.

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Granular Age Prediction Analysis in Online Gaming: Insights from Player Data

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  1. Age Prediction GroupAnalysis 11 August 2, 2010 Brooke, Kyong, Robby, Tracy, Tommy, Jaideep

  2. Outline • We perform more model building exercise. In this analysis, we further divide into more granular age ranges  Model 7 • player level • race • gender • class • guild rank • education • employment • number of characters per account • total number of hours playing EQ II (play1) • total number of PvP kills • Total number of PvP kills and Total number of play time were extracted from Nagafen server.

  3. Age Group Breakdown • Three age groups • Group 1: AGE <= 17 • Group 2: 18 <= AGE <= 22 • Group 3: 23 <= AGE <= 36 • Group 4: 37 <= AGE <= 45 • Group 5: 46 <= AGE <= 60 • Group 6: AGE >= 61

  4. Age Group Breakdown 2 • Three age groups • Group 1: AGE <= 17 • Group 2: 18 <= AGE <= 22 • Group 3: 23 <= AGE <= 27 • Group 4: 28<= AGE <= 36 • Group 5: 37<= AGE <= 45 • Group 6: AGE >= 46

  5. Model 7 Precision# correct results / # all returned results Recall# correct results / # all results that should have been returned F-Measureharmonic mean of Precision and Recall

  6. Model 7 F-Measureharmonic mean of Precision and Recall

  7. Appendix • Model 4 • Model 5 • Model 6

  8. Model 5 (PvP kills extracted from Nagafen) Precision# correct results / # all returned results Recall# correct results / # all results that should have been returned F-Measureharmonic mean of Precision and Recall

  9. Model 4 (PVP kills) Precision# correct results / # all returned results Recall# correct results / # all results that should have been returned F-Measureharmonic mean of Precision and Recall

  10. Model 6 Precision# correct results / # all returned results Recall# correct results / # all results that should have been returned F-Measureharmonic mean of Precision and Recall

  11. Model 6 F-Measureharmonic mean of Precision and Recall

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