Play-Persona: Modeling Player Behaviour in Computer Games

More documents

Recommendations

Info

foreshadowing of a reader competent enough to provide the best interpretation of a text”. The author tries to prefigure a model reader by imagining what could be the actualization of the text. The author, consciously or not, is concerned with how the text / type becomes interpretation / token. In social sciences, Max Weber introduced the concept of Idealtyp as: “Formed by one-sided accentuation of one or more points of view and by the synthesis of a great many diffuse, discrete, more or less present and occasionally absent concrete individual phenomena, which are arranged according to those one-sidedly emphasized viewpoints into a unified analytical construct” [20]. The ideal type is a pure mental construct used to assess the behaviour of social groups. It is totally theoretic, almost fictitious and generally not empirically found anywhere in reality, it is not backed by statistical data nor a model personality profile, it is more used as some sort of unit of measure, standards much like "meter", "second" or "kilogram" not really found in nature, but useful to measure it. In similar ways game designers could benefit greatly by making assumptions on the nature of players using personas to map the extreme boundaries of the field of possibilities afforded by their game. 2.2 Traditional persona modeling Alan Cooper’s [3] goal directed design process starts with the research phase, in which behaviours patterns and modes of use of products are identified. These patterns suggest goals and motivations and in turn these inform the creation of personas. Personas are detailed, composite user archetypes and they serve as main characters in narrative, scenario-based descriptions that iteratively inform the design of a product, so that features emerge directly from the goals. Typically a persona is a description of behaviour patterns, goals, skills, attitudes, and environment, with a few fictional personal details to make it a realistic character. For each product there should be set of 3 to 12 personas, it is not necessary to design for all of them, but an extensive cast helps articulate the user population, the primary focus for the design will be a limited subset of maximum three personas. Persona description should be precise including as many details as possible, but not necessarily accurate, it does not need to represent a real person. Name, physical appearance, education, and idiosyncrasies should be included. The main benefits of personas for product development purposes are: A) It is easier to relate to a personal human face and name instead of abstract customer data. 150
B) It is possible to infer user needs not openly stated by drawing on personal people-experience. C) Personas provide a shared, fast and effective language for communication between engineers and designers. D) Personas states what a user needs and wants so that no stakeholder can reshape the user to their convenience. E) Personas avoids self-referential designs, where designers might unconsciously project own mental models. F) Personas also work as reality-checks, helping designers keeping the focus on the limited subset of users that have been deemed “primary”. G) Proposed designs, features and solutions can be evaluated against the needs of individual persona models. Personas have also been criticized mostly because if they are fictional, they have no clear relationship to real customer data and therefore any data gathered cannot be considered scientific [1]. In any case, in order to apply this design method to computer games some changes are necessary. 3 FROM PERSONA TO PLAY-PERSONA Play-personas are further defined as clusters of preferential interaction (what) and navigation (where) attitudes, temporally expressed (when), that coalesce around different kinds of inscribed affordances in the artefacts provided by game designers. This means that personas can no longer just be limited to narrative descriptions of motivations, needs and desires distilled in ethnographic interviews. The persona hypotheses emerge as a relation of parameters from the set of interaction and navigation possibilities that the game-rules and game spaces can afford [22]. Personas can be augmented and strengthened by a quantifiable, parametric, data-driven perspective. Furthermore, if directly coupled with instrumentation data in the form of gameplay metrics gathered from game engine software during play sessions, play-personas can provide a powerful evaluation tool to confirm whether a certain hypothesis also turns out to represent a sizeable slice of players. That is why play-personas are both theoretical models of ideal users (metaphor) and data-driven representations of player behaviours (lens). 151
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
Page 33:
Following the humanistic tradition
Page 36 and 37:
In most games it is not realistic t
Page 38 and 39:
ehaviour. Assessing assumptions on
Page 40 and 41:
Independently on the identity of ea
Page 42 and 43:
main focus of the brand has always
Page 44 and 45:
3.4 Play-persona as a lens (a poste
Page 46 and 47:
Figure 10: personality and subperso
Page 49 and 50:
4. CREATING EXPERIENCES The MDA fra
Page 51 and 52:
Play-styles are sets of isotopic ga
Page 53 and 54:
4.2.3 Player expression Player expr
Page 55:
Players will eventually understand
Page 58 and 59:
Combining both of these two approac
Page 61 and 62:
REFERENCES 1. Aarseth, E. (1997): C
Page 63 and 64:
52. Hunicke, R. LeBlanc, M. & Zubek
Page 65:
96. Wiggins, A. (2006): Data Driven
Page 69 and 70:
ARTICLE 1 - TOWARDS A THEORY OF THE
Page 71 and 72:
flow between the player, the avatar
Page 73 and 74:
6. The player constructs knowledge
Page 75 and 76:
are sets of rational, bodily, and b
Page 77 and 78:
ehaviorism asserting that a compreh
Page 79 and 80:
4.3 Origin of subpersonalities Acco
Page 81 and 82:
environment and the emanating subpe
Page 83 and 84:
flow line), one must increase the c
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
Page 99 and 100: gather info, spying through keyhole
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
Page 109 and 110: esults in the relatively easy task
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 and 124: of non lethal, silent, and clean de
Page 125 and 126: ARTICLE 5 - DEFINING PERSONAS IN GA
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: experiences are evaluated and remem
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
Page 175 and 176: titles where there is a trend towar
Page 177 and 178: a secondary variable together with
Page 179 and 180: player spent at the location and wh
Page 181 and 182: 3. Börner, K., Penumarthy, S.: Soc
Page 183 and 184: 34. Thompson, C.: Halo 3: How Micro
Page 185 and 186: ARTICLE 8 - ANALYZING SPATIAL USER
Page 187 and 188: on basic statistical analysis metho
Page 189 and 190: visualization or for creating overv
Page 191 and 192: egarding actions undertaken in-game
Page 193 and 194: ased methods within the games area
Page 195 and 196: 2.4 The EIDOS Metrics Suite The dat
Page 197 and 198: is played in Third-Person perspecti
Page 199 and 200: one cause of death, and performing
Page 201 and 202:
ArcGIS permits different layers to
Page 203 and 204:
4. Cadez, I., Heckerman, D., Meek,
Page 205 and 206:
35. Whiteside, J., Archer, N. P., W
Page 207 and 208:
ARTICLE 9 - PLAYER MODELING USING S
Page 209 and 210:
unsupervised learning in capturing
Page 211 and 212:
3. TOMB RAIDER: UNDERWORLD The popu
Page 213 and 214:
2 - Environment; the percent of tot
Page 215 and 216:
(ESOM) [5] to emphasize the distinc
Page 217 and 218:
populated middle-left cluster (Fig.
Page 219 and 220:
weight values we repeat the trainin
Page 221 and 222:
TABLE I THE FOUR PLAYING BEHAVIOR C
Page 223 and 224:
(d) Number of Deaths, D (e) Complet
Page 225 and 226:
equests for specific in-game puzzle
Page 227 and 228:
13. G. N. Yannakakis and M. Maragou
Page 229 and 230:
ARTICLE 10 - PSYCHOLOGY OF PERSONAL
Page 231 and 232:
Personality is described as recogni
Page 233 and 234:
Inputs: Outputs: Primary attack (ra
Page 235 and 236:
Due to the fact that each game metr
Page 237 and 238:
12. Jennett, C., Cox, A.L., Cairns,
Page 239 and 240:
ARTICLE 11 - GAME METRICS AND BIOME
Page 241 and 242:
His research interests are biometri
Page 243 and 244:
5. R. L. Hazlett. Measuring emotion
Page 245 and 246:
ARTICLE 12 - ANALYZING USER BEHAVIO
Page 247 and 248:
elated to player-game interaction a
Page 249 and 250:
10. Kuniavsky, M.: Observing the Us
Page 251 and 252:
ARTICLE 13 - PATTERNS OF PLAY: PLAY
Page 253 and 254:
Play-personas are here introduced a
Page 255 and 256:
It is only natural that game design
Page 257 and 258:
4 Defining play-personas using game
Page 259 and 260:
TRU is the eighth installment in th
Page 261 and 262:
gameplay, descriptiveness of player
Page 263 and 264:
In the case of TRU, the three param
Page 265 and 266:
into which sections of the levels t
Page 267 and 268:
Runners: This group completes the g
Page 269 and 270:
17. Iser, W.: The Implied Reader. J
show all

Play-Persona: Modeling Player Behaviour in Computer Games

You also want an ePaper? Increase the reach of your titles

Delete template?

Save as template?