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  1. Personification: Metaphor and Fictional Character in CMC Johan F. Hoorn tion Association International Commun Vrije Universiteit Faculty of Sciences, Department of Computer Science Section Information Management & Software Engineering Subsection Human Computer Interaction, Multimedia & Culture jfhoorn@cs.vu.nl May 25, 2003 San Diego, CA www.cs.vu.nl/~jfhoorn

  2. Theory Personification, what is it?

  3. Personification Fictional character (Time, Cupid) used as a metaphor (Time is a man, Love is a boy) for an abstraction (Time, Love) Pierre Mignard (1694). Time Clipping Cupid’s Wings.

  4. Personification Fictional character (Robby) used as a metaphor (Human is machine) for an abstraction (Help, Search, Navigate) Software agents can be personifications Bill Gates (1997). Robby the Robot.

  5. No Personification Fictional character (Builder) used literally (Builder is a tutor) for an abstraction (Help, Instruct, Create) For this agent, the metaphoric aspect is missing RealTimeAide (2003). Building tutor. http://www.realtimeaide.com/tutor/tutor.htm

  6. Research question What’s the use of personification in CMC?

  7. Should we apply personifications? User effort Motivation Literal icon/dialog Metaphoric icon/dialog Mediated person/ Fictional character (FC) Personification (FC plus metaphor) Ease of understanding Fun Task relevance User support “Look and feel” Etc.

  8. Personification is more effort for more motivation? Should we apply personifications? User effort Motivation Literal icon/dialog +(easy) - (no fun) Metaphoric icon/dialog - (difficult) + (surprising) Mediated person/ - (build a ++ (involve- Fictional character (FC) relationship) ment) Personification - - +++ (FC plus metaphor)

  9. Theory Agents, what do they communicate?

  10. Agent-Mediated Communication Sender Message Receiver System’s stakeholder (e.g., client, designer, manager) End-user Fictional character + metaphor Goals: - be instructed - be persuaded - be entertained Goals: - instruct - persuade - entertain Match?

  11. Agent-Mediated Communication Sender Message Receiver’s perspective System’s stakeholder (e.g., client, designer, manager) End-user Fictional character Human processing Support user goals? PEFiC + metaphor Goals: - instruct - persuade - entertain yes no Use agent Don’t use agent Metaphor process

  12. Agent-Mediated Communication Sender’s perspective Message Receiver System’s stakeholder (e.g., client, designer, manager) End-user Alter agent no Support other goal? Goals: - be instructed - be persuaded - be entertained Goals: - instruct - persuade - entertain yes no Match? yes Maintain agent http://www.csc.ncsu.edu/eos/users/l/lester/www/images/IPA/cosmo_ok.gif

  13. Agent-Mediated Communication Sender Message Receiver’s perspective End-user Perceiving and Experiencing Fictional Characters Human processing PEFiC For empirical evidence, see and hear:

  14. Results of other studies Characters, how are they processed?

  15. ENCODE COMPARE RESPOND Involvement % Ethics dissimilar good irrelevant beautiful negative valence realistic Features of situation and Fictional Character Aesthetics Appreciation similar bad relevant ugly positive valence Epistemics unrealistic Norm Distance % Identification, empathy, sympathy, warm feelings, approach, etc. Appraisal domains Fuzzy feature sets Mediators Subjective norm vs. group norm Detachment, antipathy, cold feelings, avoidance, etc. PEFiC model

  16. Distance Example of PEFiC in action for factor Relevance to user goals Involvement Peedy Relevant features if goal is ‘entertainment’ Task-irrelevant features (goal ‘instruction’) http://www.scpcug.com/wmwand12.html

  17. From character to metaphor What is the role of epistemics?

  18. Agent-Mediated Communication Message Receiver’s perspective End-user Race model of Metaphor Processing Human processing Part of Epistemics RMP For empirical evidence, see:

  19. Metaphor is part of Epistemics ‘tutor is a human’ ‘human is a machine’ suit ‘conversation partner is a human’ ‘product presenter is a dog’’ constrained feet drooling drooling (too enthusiastic) (saliva) descriptive figurative descriptive figurative descriptive figurative descriptive figurative literal metaphor literal metaphor unrealistic realistic COMMUNICATION FORM EPISTEMICS ASSOCIATION http://www.ics.uci.edu/~kobsa/courses/ICS104/course-notes/metaphors.ht; http://www.techfak.uni-bielefeld.de/ags/wbski/lehre/digiSA/Methoden_der_KI/WS0102/methki15.pdf

  20. Results of other studies Metaphors, how are they processed?

  21. Calculate descriptive intersection Activate descriptive and figurative features Activate descriptive and figurative features human machine Category match? no yes Calculate descriptive/figurative intersection EEG: N400 at frontal cortex feet constrained Race model of Metaphor Processing Sufficient descriptive AND descriptive/figurative intersection? no ‘Anomaly’ Cosmo Sufficient descriptive/figurative intersection? no yes ‘Literal’ ‘Metaphor’

  22. Discussion How come metaphors are harder to get but do not take more time? Errors are the answer

  23. Calculate descriptive intersection Problem: Response times for literal and metaphor are about equal. No way telling whether these two information sources are serial or parallel Calculate descriptive/figurative intersection (1) (2) If serial (1 before 2), applying metaphor is more time consuming and probably, more difficult to understand If parallel, metaphor can be applied without losing time-efficiency and trouble of understanding Sufficient descriptive/figurative intersection? no yes ‘Literal’ ‘Metaphor’

  24. Calculate descriptive intersection Solution: Investigate Lateralized Readiness Potential (LRP) in response to partial error pattern (after Coles et al., 1995) Thus, speed is not the difficulty in metaphor but accuracy is Calculate descriptive/figurative intersection (1) (2) Many errors for ‘Literal’  invisible in behavioral measures (e.g., RT) because they are corrected before response execution  visible in EEG Few errors for ‘Metaphor’ ‘Literal’ ‘Metaphor’ For full argumentation, see:

  25. Predictions for contralateral effects of finger movement during metaphor processing (fictitious data) Partial error ‘Literal’ Correct ‘Metaphor’ LRP high LRP low motor cortex stimulus onset stimulus onset stimulus response buttons ‘Metaphor’ ‘Literal’

  26. Shall we apply personifications, then? high User effort Motivation Literal icon/dialog +(easy) - (no fun) Metaphoric icon/dialog - (difficult) + (surprising) Mediated person/ - (do I like the ++ (personal Fictional character (FC) character?) -ized) Personification- - +++ (FC plus metaphor) high N400 (surprise) Two information sources: - descriptive - descriptive/figurative Time efficiency Category mismatch Error prone (LRP) PEFiC RMP Appreciation (Fun) Task relevance Valence (User support) Aesthetics (“Look and feel”) Ethics (Good bot vs. bad bot) Epistemics (Graphic rendering) Similarity (cf. Avatars) Involvement-distance Personification is more effort for more motivation

  27. Future work We developed a software package for testing existing and newly created agents: Stimulus and trial production, RTs, and in the future, questionnaires and EEG extensions. Downloads: http://www.antbed.tk/

  28. What is it? What can you do with it?

  29. Action preview Create environments in PowerPoint and let the agent do its actions

  30. Personification: Metaphor and Fictional Character in CMC THE END Wanna know more? Visit www.cs.vu.nl/~jfhoorn