Automatic Annotation of Characters’ Emotions in Stories

  • Vincenzo Lombardo
  • Rossana Damiano
  • Cristina Battaglino
  • Antonio Pizzo
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9445)


The emotional states of the characters allow the audience to understand their motivations and feel empathy for their reactions to the story incidents. Consequently, the annotation of characters’ emotions in narratives is highly relevant for story indexing and retrieval but also editing and analysis. In this paper, we address the construction of tools for the annotation of characters’ emotions in stories, opening the way to the construction of a corpus of narratives annotated with emotions.


Emotion annotation Narrative corpora Emotion appraisal 


  1. 1.
    Quesenberry, K.A., Coolsen, M.K.: What makes a super bowl ad super? five-act dramatic form affects consumer super bowl advertising ratings. J. Mark. Theory Pract. 22(4), 437–454 (2014)CrossRefGoogle Scholar
  2. 2.
    Battaglino, C., Damiano, R.: Emotional appraisal of moral dilemma in characters. In: Oyarzun, D., Peinado, F., Young, R.M., Elizalde, A., Méndez, G. (eds.) Interactive Storytelling. Lecture Notes in Computer Science, vol. 7648, pp. 150–161. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  3. 3.
    Battaglino, C., Damiano, R., Lesmo, L.: Emotional range in value-sensitive deliberation. In: AAMAS, pp. 769–776 (2013)Google Scholar
  4. 4.
    Bratman, M.: Intention, Plans, and Practical Reason. Harvard University Press, Cambridge (1987)Google Scholar
  5. 5.
    Cohen, P.R., Levesque, H.J.: Intention is choice with commitment. Artif. Intell. 42, 213–261 (1990)CrossRefMathSciNetzbMATHGoogle Scholar
  6. 6.
    Dias, J., Mascarenhas, S., Paiva, A.: Fatima modular: towards an agent architecture with a generic appraisal framework. In: Workshop on Standards in Emotion Modeling. Leiden (2011)Google Scholar
  7. 7.
    Elliott, C.D.: The Affective Reasoner: A Process Model of Emotions in a Multi-agent System. Ph.D. thesis, Northwestern University, Evanston, IL, USA (1992). UMI Order No. GAX92-29901Google Scholar
  8. 8.
    Elson, D.: Dramabank: Annotating agency in narrative discourse. In: LREC, pp. 2813–2819 (2012)Google Scholar
  9. 9.
    Fairclough, C.R., Cunningham, P.: A multiplayer opiate. Int. J. Intell. Games Simul. 3(2), 54–61 (2004)Google Scholar
  10. 10.
    Gebhard, P.: Alma: a layered model of affect. In: Proceedings of the Fourth International Joint Conference on Autonomous Agents and Multiagent Systems, pp. 29–36. ACM (2005)Google Scholar
  11. 11.
    Gervás, P.: Propp’s morphology of the folk tale as a grammar for generation. In: CMN, p. 106–122 (2013)Google Scholar
  12. 12.
    Horrocks, I., Patel-Schneider, P.F., Boley, H., Tabet, S., Grosof, B., Dean, M., et al.: Swrl: A semantic web rule language combining owl and ruleml. W3C Member submission 21, 79 (2004)Google Scholar
  13. 13.
    Lombardo, V., Damiano, R.: Commonsense knowledge for the collection of ground truth data on semantic descriptors. In: Proceedings of the 2012 IEEE International Symposium on Multimedia (ISM 2012), pp. 78–83. IEEE Computer Society (2012)Google Scholar
  14. 14.
    Lombardo, V., Pizzo, A.: Multimedia tool suite for the visualization of drama heritage metadata. Multimedia Tools and Applications pp. 1–32 (2014)Google Scholar
  15. 15.
    Lombardo, V., Pizzo, A.: Ontology–based visualization of characters’ intentions. In: Mitchell, A., Fernández-Vara, C., Thue, D. (eds.) Interactive Storytelling. Lecture Notes in Computer Science, vol. 8832, pp. 176–187. Springer, Heidelberg (2014)Google Scholar
  16. 16.
    Marsella, S.C., Gratch, J.: Ema: a process model of appraisal dynamics. Cogn. Syst. Res. 10(1), 70–90 (2009)CrossRefGoogle Scholar
  17. 17.
    Marsella, S.C., Gratch, J., Petta, P.: Computational models of emotion. In: Scherer, K.R., BÃnziger, T., Roesch (eds.) A Blueprint for an Affectively Competent Agent: Cross-Fertilization Between Emotion Psychology, Affective Neuroscience, and Affective Computing. Oxford University Press, Oxford (2010).
  18. 18.
    Norling, E., Sonenberg, L.: Creating interactive characters with BDI agents. In: Proceedings of the Australian Workshop on Interactive Entertainment IE2004 (2004)Google Scholar
  19. 19.
    Ortony, A., Clore, G., Collins, A.: The Cognitive Structure of Emotions. Cambrigde University Press, Cambrigde (1988)CrossRefGoogle Scholar
  20. 20.
    Peinado, F., Cavazza, M., Pizzi, D.: Revisiting character-based affective storytelling under a narrative BDI framework. In: Spierling, U., Szilas, N. (eds.) Interactive Storytelling. Lecture Notes in Computer Science, vol. 5334, pp. 83–88. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  21. 21.
    Plantinga, C.: Moving Viewers: American Film and the Spectator’s Experience. Univ of California Press, Berkeley (2009)Google Scholar
  22. 22.
    Propp, V.: Morphology of the Folktale. University of Texas Press, Austin (1968)Google Scholar
  23. 23.
    Rank, S., Petta, P.: Appraisal for a character-based story-world. In: Panayiotopoulos, T., Gratch, J., Aylett, R.S., Ballin, D., Olivier, P., Rist, T. (eds.) Intelligent Virtual Agents. Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence), vol. 3661, pp. 495–496. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  24. 24.
    Reilly, W.S.: Believable social and emotional agents. Technical report, DTIC Document (1996)Google Scholar
  25. 25.
    Rishes, E., Lukin, S.M., Elson, D.K., Walker, M.A.: Generating different story tellings from semantic representations of narrative. In: Koenitz, H., Sezen, T.I., Ferri, G., Haahr, M., Sezen, D., C̨atak, G. (eds.) Interactive Storytelling. Lecture Notes in Computer Science, vol. 8230, pp. 192–204. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  26. 26.
    Steunebrink, B.R., Dastani, M., Meyer, J.J.C.: The occ model revisited. In: Proceedings of the 4th Workshop on Emotion and Computing (2009)Google Scholar
  27. 27.
    Thompson, S.: Myths and folktales. J. Am. Folklore 68(270), 482–488 (1955)CrossRefGoogle Scholar
  28. 28.
    Zarri, G.P.: Conceptual and content-based annotation of (multimedia) documents. Multimedia Tools Appl. 72(3), 2359–2391 (2014)CrossRefGoogle Scholar
  29. 29.
    Zarri, G.P.: Sentiments analysis at conceptual level making use of the narrative knowledge representation language. Neural Netw. 58, 82–97 (2014)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Vincenzo Lombardo
    • 1
  • Rossana Damiano
    • 1
  • Cristina Battaglino
    • 1
  • Antonio Pizzo
    • 2
  1. 1.Department of Computer Science and CIRMAUniversity of TorinoTurinItaly
  2. 2.Department of Humanities and CIRMAUniversity of TorinoTurinItaly

Personalised recommendations