- Page 1: Play-Persona: Modeling Player Behav
- Page 4 and 5: 4.2.3 PLAYER EXPRESSION 53 4.3 PEIR
- Page 7 and 8: ACKNOWLEDGEMENTS I would like to th
- Page 9: ABSTRACT This thesis proposes a fra
- Page 12 and 13: Analysis seeks to break down comple
- Page 14 and 15: Considering games as acts of commun
- Page 16 and 17: ensemble - the syntagm. Selection r
- Page 18 and 19: described in terms of likelihood of
- Page 20 and 21: ook: FLUX, published in 2008. This
- Page 23 and 24: 2. A THEORETICAL FRAMEWORK FOR MODE
- Page 25 and 26: “positivism” and “anti-positi
- Page 27 and 28: with the game world based solely on
- Page 29 and 30: on that text. Later, Barthes introd
- Page 31 and 32: according to their mental state. Wh
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- Page 36 and 37: In most games it is not realistic t
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- Page 40 and 41: Independently on the identity of ea
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- Page 44 and 45: 3.4 Play-persona as a lens (a poste
- Page 46 and 47: Figure 10: personality and subperso
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- Page 57 and 58: 5. CONCLUSIONS AND FUTURE WORK This
- Page 59: 5.1.2 Applications of play-personas
- Page 62 and 63: 25. Computational Intelligence and
- Page 64 and 65: 76. Norman, D. (1999): The Invisibl
- Page 67: Compendium Articles 67
- Page 70 and 71: patterns are of an emotional, ratio
- Page 72 and 73: FIGURE 1 Perceptive and Reflective
- Page 74 and 75: Candace Pert is the neuroscientist
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- Page 78 and 79: 4.2 PSYCHOSYNTHESIS Psychosynthesis
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- Page 84 and 85: Following up the “soft edges” m
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- Page 90 and 91: 33. THAGARD, P. & BARNES, A. Emotio
- Page 92 and 93: 1 INTRODUCTION Fig. 1 Player, actio
- Page 94 and 95: 3 AESTHETIC ANALYSIS 3.1 Histograms
- Page 96 and 97: 4 ARCHITECTURAL ANALYSIS 4.1 Macro
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threshold. For the “Loading” ar
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6 PHENOMENOLOGICAL ANALYSIS 6.1 Pla
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lood pressure. Through their patent
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REFERENCES 1. Carson, D. Environmen
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As a possible way out from this imp
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perfect in order to obtain an in-de
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Lindley defines play-gestalts as pa
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schema) are nearly identical, but t
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6 PLAY-PERSONAS When a player behav
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116
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2 Computer games and game metrics C
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Designers can use personas as categ
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Play or blending in; it consists of
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7 Conclusions The play-persona fram
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early example of Deus Ex, a First-P
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designed to a specific subject area
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interact with objects and entities
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Table 1: A model of the full range
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Figure 3: (left): Tracking the move
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Appearance Hitman: Blood Money feat
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the requirements of the analysis in
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5. USING PERSONAS: “Hitman: Blood
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Interaction possibility field: Ther
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generated content and flow maintena
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146
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way to express themselves. For exam
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foreshadowing of a reader competent
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3.1 Gameplay metrics Gameplay metri
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of discovering patterns in the usag
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4.1 Grunt persona Narrative descrip
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Fig. 5: Personas as lenses show the
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type of games would not particularl
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17. Ravaja, N., Saari, T., Laarni,
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increasing complexity of contempora
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of user behavior via gameplay metri
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In terms of using gameplay metrics
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custom in house-produced tool which
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In the map level selected for this
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gameplay metrics cannot inform abou
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Figure 4: Screenshot from Kane & Ly
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Figure 5: The path of the tester ha
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use of game metrics for gameplay an
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19. Jørgensen, A. H.: Marrying HCI
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184
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The methods currently employed for
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is a computerized data management s
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fair degree of precision, e.g. repo
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only rarely done. One of the few pu
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which can subsequently be analyzed
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3. TOMB RAIDER: A CASE STUDY To sho
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Figure 4: Grid-based heatmap of the
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Figure 7: Detail of the overlay ana
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user research experts in game devel
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19. Korhonen, H., Koivisto, E.M.I.:
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206
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Within the last five years, instrum
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ehaviors in Quake II while White an
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Note that at the moment of writing
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6) Help-on-Demand: The number of ti
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7. RESULTS This section presents th
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7.2 ESOM Fig. 4. Rectangular lattic
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areas represent relatively large va
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(a) Cause of Death: Opponent, Do (b
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8. DISCUSSION & CONCLUSIONS This pa
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REFERENCES 1. K. Isbister and N. Sc
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228
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fear”). The German terms “erfah
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There are only few ways to move and
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game variables should be monitored
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References 1. Bartle R.A. Player wh
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23. Nijholt, A., BCI for Games: A
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1. INTRODUCTION In the past, user-c
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3. POINTS OF INTERACTIVITY Each pan
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14. L. Nacke, C. Lindley, and S. St
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interaction options between the use
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Gameplay metrics form a novel appro
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250
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greater degree, as is evidenced by
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cognitive imperative, an innate nee
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3.1 From personas to Play-personas
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gameplay metrics data gathered from
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considered to be pre-linguistic and
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enemies, the number of times a weap
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million. Every time players ask for
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In a quantitative approach towards
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preliminary hypothesis of in-game b
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40. Davis, J.; Steury, K., Pagulaya