Play-Persona: Modeling Player Behaviour in Computer Games

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7 Conclusions The play-persona framework aggregates data in a way that binds ludic and narrative aspects of the game. It allows designers to expand their role from mere dealers of rewards and punishments, disseminating challenges and skills for a general undistinguished audience, to become crafters, orchestrators of experiences, weavers of playing modes. 124
ARTICLE 5 - DEFINING PERSONAS IN GAMES USING METRICS This article, written in cooperation with Anders Tychsen (ITU), has been presented at Futureplay 2008 and published in the ACM digital library. ABSTRACT Game metrical data are increasingly being used to enhance game testing and to inform game design. There are different approaches and techniques to gather the metrics data; however there seems to be a lack of frameworks to read and make sense of it. In this paper, the concept of play- persona is applied to game metrics, in the specific case of character-based computer games, where the player controls a single protagonist, around whom the gameplay and –story evolves. A case is presented for Hitman: Blood Money (IO Interactive, 2007). Player-controlled game characters can be deconstructed into a range of components and these expressed as monitored game metrics. These metrics can subsequently be utilized to discover patterns of play by building play-personas: Modeled representations of how players interact with the game. This process can also be useful to assist game design, by informing whether the game facilitates the specific play patterns implied by theoretical play-personas. Categories and Subject Descriptors K.8 [Personal computing]: Games; J.4 [Social and Behavioral Sciences]: Psychology. General Terms Measurement, Design, Human Factors, Theory. Keywords Persona, character, metrics, instrumentation, game design 1 INTRODUCTION The reasons why people play games are many [1], and therefore the ways that they play are different. Although game design places limits on the way games can be played, it is an increasingly important paradigm that games should be able to be played in many different ways [20]. With the 125
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Play-Persona: Modeling Player Behav
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4.2.3 PLAYER EXPRESSION 53 4.3 PEIR
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ACKNOWLEDGEMENTS I would like to th
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ABSTRACT This thesis proposes a fra
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Analysis seeks to break down comple
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Considering games as acts of commun
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ensemble - the syntagm. Selection r
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described in terms of likelihood of
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ook: FLUX, published in 2008. This
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2. A THEORETICAL FRAMEWORK FOR MODE
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“positivism” and “anti-positi
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with the game world based solely on
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on that text. Later, Barthes introd
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according to their mental state. Wh
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Following the humanistic tradition
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In most games it is not realistic t
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ehaviour. Assessing assumptions on
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Independently on the identity of ea
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main focus of the brand has always
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3.4 Play-persona as a lens (a poste
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Figure 10: personality and subperso
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4. CREATING EXPERIENCES The MDA fra
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Play-styles are sets of isotopic ga
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4.2.3 Player expression Player expr
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Players will eventually understand
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Combining both of these two approac
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REFERENCES 1. Aarseth, E. (1997): C
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52. Hunicke, R. LeBlanc, M. & Zubek
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96. Wiggins, A. (2006): Data Driven
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ARTICLE 1 - TOWARDS A THEORY OF THE
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flow between the player, the avatar
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Page 75 and 76: are sets of rational, bodily, and b
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Page 79 and 80: 4.3 Origin of subpersonalities Acco
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Page 85 and 86: 7.1 Explorer’s path FIGURE 5 Expl
Page 87 and 88: the roof section, where he/she will
Page 89 and 90: 14. DE SOUSA, R. 2003. Emotions. In
Page 91 and 92: ARTICLE 2 - DESIGNING LEVELS FOR EN
Page 93 and 94: 2 STRUCTURE OF A GAME LEVEL The fir
Page 95 and 96: 3.2 Symbolical Reading The movement
Page 97 and 98: The hangar is open for workers and
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Page 101 and 102: 6.2 Play-Personas I am going to def
Page 103 and 104: The Butcher persona would have quit
Page 105 and 106: ARTICLE 3 - WAVING EXPERIENCES: PLA
Page 107 and 108: types" [12]. Personas are construct
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Page 111 and 112: Crew actions schemas are: • Squad
Page 113 and 114: choice given until the mark “poli
Page 115 and 116: REFERENCES 1. Bozec, P. "My Everyth
Page 117 and 118: ARTICLE 4 - WEAVING EXPERIENCES IN
Page 119 and 120: In order to be able to take acti
Page 121 and 122: persona could be narratively define
Page 123: of non lethal, silent, and clean de
Page 127 and 128: software is however limited in that
Page 129 and 130: event sets, i.e. capturing metrical
Page 131 and 132: objects and entities within it. Eve
Page 133 and 134: metrics include tracking camera vie
Page 135 and 136: Figure 4: Example of interaction me
Page 137 and 138: looting is a play-style observed in
Page 139 and 140: players can choose between differen
Page 141 and 142: Play modes: Running, climbing, fall
Page 143 and 144: according to their positioning on a
Page 145 and 146: 14. Medlock, M.C., Wixon, D.; Terra
Page 147 and 148: ARTICLE 6 - PLAY-PERSONAS: BEHAVIOU
Page 149 and 150: experiences are evaluated and remem
Page 151 and 152: B) It is possible to infer user nee
Page 153 and 154: personas are hypotheses that emerge
Page 155 and 156: Expert Rookie Grunt Athlete Chess-
Page 157 and 158: Procedural description: Shooting: -
Page 159 and 160: In the case example for Tomb Raider
Page 161 and 162: 2. Cooper, A.: The Inmates Are Runn
Page 163 and 164: ARTICLE 7 - TOWARDS GAMEPLAY ANALYS
Page 165 and 166: The requirement for improving user-
Page 167 and 168: The literature on game metrics is m
Page 169 and 170: ecause they all stem from in-house
Page 171 and 172: If a player kills a traitor they re
Page 173 and 174: Figure 3 (Top): diagram showing the
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titles where there is a trend towar
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a secondary variable together with
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player spent at the location and wh
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3. Börner, K., Penumarthy, S.: Soc
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34. Thompson, C.: Halo 3: How Micro
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ARTICLE 8 - ANALYZING SPATIAL USER
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on basic statistical analysis metho
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visualization or for creating overv
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egarding actions undertaken in-game
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ased methods within the games area
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2.4 The EIDOS Metrics Suite The dat
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is played in Third-Person perspecti
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one cause of death, and performing
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ArcGIS permits different layers to
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4. Cadez, I., Heckerman, D., Meek,
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35. Whiteside, J., Archer, N. P., W
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ARTICLE 9 - PLAYER MODELING USING S
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unsupervised learning in capturing
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3. TOMB RAIDER: UNDERWORLD The popu
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2 - Environment; the percent of tot
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(ESOM) [5] to emphasize the distinc
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populated middle-left cluster (Fig.
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weight values we repeat the trainin
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TABLE I THE FOUR PLAYING BEHAVIOR C
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(d) Number of Deaths, D (e) Complet
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equests for specific in-game puzzle
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13. G. N. Yannakakis and M. Maragou
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ARTICLE 10 - PSYCHOLOGY OF PERSONAL
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Personality is described as recogni
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Inputs: Outputs: Primary attack (ra
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Due to the fact that each game metr
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12. Jennett, C., Cox, A.L., Cairns,
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ARTICLE 11 - GAME METRICS AND BIOME
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His research interests are biometri
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5. R. L. Hazlett. Measuring emotion
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ARTICLE 12 - ANALYZING USER BEHAVIO
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elated to player-game interaction a
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10. Kuniavsky, M.: Observing the Us
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ARTICLE 13 - PATTERNS OF PLAY: PLAY
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Play-personas are here introduced a
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It is only natural that game design
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4 Defining play-personas using game
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TRU is the eighth installment in th
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gameplay, descriptiveness of player
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In the case of TRU, the three param
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into which sections of the levels t
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Runners: This group completes the g
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17. Iser, W.: The Implied Reader. J
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