skip to main content
10.1145/2797143.2797174acmotherconferencesArticle/Chapter ViewAbstractPublication PageseannConference Proceedingsconference-collections
research-article

House of Ads: a Multiplayer Action Game for Annotating Ad Video Content

Authors Info & Claims
Published:25 September 2015Publication History

ABSTRACT

Content-based search in a large collection of media is a task that cannot be fully automated. Semantic annotations provided by humans through crowdsourcing techniques can be attached to media elements in the form of metadata and be used by search engines to provide the required results. However, the manual annotation of large collections is a tedious and time-consuming process and proper incentives need to be provided to attract contributors. Games with a purpose, or human computation games are based on the idea that people could solve computational tasks while playing online games. Numerous such games have been created and used in various areas, including media annotation. However, the majority of them contain limited game elements and the main challenge is the annotation task itself. This paper presents the design, implementation and early evaluation of a human computation game for supporting creative advertising. The game is part of a larger project for data mining and content-based searching in a rich collection of video ads aiming to serve as a creativity support tool for advertisers. Its main aim is to have players populate an ontology whilst playing a multiplayer game that includes an action and a quiz gameplay mode. The game incorporates a variety of elements and challenges found in modern action games and uses a metaphor of rooms and collectible items to represent the ontology concepts in the game world. The pilot study results indicate that players found the concept interesting, but there is still room for improvements in the gameplay and appearance.

References

  1. Ahn, L. Von 2006. Games with a purpose. Computer. 39, 6, 96--98.Google ScholarGoogle Scholar
  2. Aitken, R., Gray, B., and Lawson, R. 2008. Advertising effectiveness from a consumer perspective. International Journal of Advertising 27(2), 279--297.Google ScholarGoogle ScholarCross RefCross Ref
  3. Amos, C, Holmes, G., and Strutton, D. 2008. Exploring the relationship between celebrity endorser effects and advertising effectiveness: A quantitative synthesis of effect size. International Journal of Advertising, 27(2), 209--234.Google ScholarGoogle ScholarCross RefCross Ref
  4. Blasko, V. and Mokwa, M. 1986. Creativity in advertising: A Janusian perspective. Journal of Advertising, 15(4), 43--72.Google ScholarGoogle ScholarCross RefCross Ref
  5. Burke, R.R., Rangaswamy, A., Wind, J., and Eliashberg, J. 1990. A Knowledge-Based System for Advertising Design. Marketing Science. 9, 3, 212--229.Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Carranza, J. and Krause, M. 2012. Evaluation of game designs for human computation. AAAI Workshop - Technical Report. WS-12-17, (2012), 9--15.Google ScholarGoogle Scholar
  7. Chen, Z. 2010. Computational intelligence for decision support, CRC Press (2010).Google ScholarGoogle Scholar
  8. Cuel, R. et al. 2011. Motivation mechanisms for participation in human-driven semantic content creation. International Journal of Knowledge Engineering and Data Mining. 1, 4 (2011), 331. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. ESA 2014. Annual Report.Google ScholarGoogle Scholar
  10. Goldenberg, J., Mazursky, D., and Solomon, S. 1999. The fundamental templates of quality ads. Marketing science, 18(3), 333--351. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Hill, R. and Johnson, L. 2004. Understanding creative service: a qualitative study of the advertising problem delineation, communication and response (APDCR) process. International Journal of Advertising, 23(3), 285--307.Google ScholarGoogle ScholarCross RefCross Ref
  12. Ho, C., Chang, T. H., Lee, J. C., Hsu, J. Y. J., and Chen, K. T. 2009. KissKissBan: a competitive human computation game for image annotation. Proceedings of the ACM SIGKDD Workshop on Human Computation - HCOMP '09. (2009), 11. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. Ho, C., Chang, T. H., and Hsu, J. Y. J. 2007. Photoslap: A multi-player online game for semantic annotation. Proceedings of the National Conference on Artificial Inteligence. 22, (2007), 1359. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. Hu, W., Xie, N., Li, L., Zeng, X., & Maybank, S. 2011. A survey on visual content-based video indexing and retrieval. IEEE Transactions on Systems, Man and Cybernetics Part C: Applications and Reviews. 41, 6 (2011), 797--819. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. Kermanidis, K. and Maragoudakis, M. 2013. Designing a Support Tool for Creative Advertising by Mining Collaboratively Tagged Ad Video Content: The Architecture of PromONTotion. Artificial Intelligence Applications and Innovations. Springer Berlin Heidelberg, 2013. 10--19.Google ScholarGoogle ScholarCross RefCross Ref
  16. Krause, M., Takhtamysheva, A., Wittstock, M., and Malaka, R. 2010. Frontiers of a Paradigm -- Exploring Human Computation with Digital Games. Proceedings of the ACM SIGKDD Workshop on Human Computation (HCOMP). (2010), 22--25. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. Law, E. and von Ahn, L. 2009. Input-agreement: a new mechanism for collecting data using human computation games. Proceedings of the 27th international conference on Human factors in computing systems - CHI 09. (2009), 1197--1206. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. Law, E.L.M., Von Ahn, L., Dannenberg, R. B., and Crawford, M. 2007. Tagatune : a Game for Music and Sound Annotation. In International Conference on Music Information Retrieval (ISMIR'07). (2007), 361--364.Google ScholarGoogle Scholar
  19. MacCrimmon, K. and Wagner, C. 1994. Stimulating ideas through creative software. Management Science, 40(11), 1514--1532. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. Maragoudakis, M., Kermanidis, K. L., and Vosinakis, S. 2014. Extracting Knowledge from Collaboratively Annotated Ad Video Content. Artificial Intelligence Applications and Innovations (pp. 85--95). Springer Berlin Heidelberg.Google ScholarGoogle Scholar
  21. Opas, T. 2008. An investigation into the development of a Creativity Support Tool for advertising. (2008).Google ScholarGoogle Scholar
  22. Pe-Than, E.P.P., Goh, D. H. L., and Lee, C. S. 2012. A survey and typology of human computation games. Proceedings of the 9th International Conference on Information Technology, ITNG 2012. May 2015 (2012), 720--725. Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. Rollings, A. and Adams, E. 2003. Andrew Rollings and Ernest Adams on game design. New Riders. Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. Rollings, A. and Morris, D. 2004. Game architecture and design: a new edition. New Riders. Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. Siorpaes, K. and Hepp, M. 2008. OntoGame: Weaving the semantic web by online games. Lecture Notes in Computer Science 5021 LNCS, (2008), 751--766. Google ScholarGoogle ScholarDigital LibraryDigital Library
  26. Thaler, S., Siorpaes, K., Mear, D., Simperl, E., and Goodman, C. 2011. SeaFish: A game for collaborative and visual image annotation and interlinking. Lecture Notes in Computer Science 6643 LNCS, PART 2 (2011), 466--470. Google ScholarGoogle ScholarDigital LibraryDigital Library
  27. Turnbull, D., Liu, R., Barrington, L., and Lanckriet, G. R. 2007. A Game-Based Approach for Collecting Semantic Annotations of Music. Ismir. (2007), 2--5.Google ScholarGoogle Scholar
  28. Wang, H., Cosley, D., and Fussell, S. R. 2010. Idea Expander: Supporting group brainstorming with conversationally triggered visual thinking stimuli. Proceedings of the 2010 ACM conference on Computer supported cooperative work (pp. 103--106). ACM. Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. House of Ads: a Multiplayer Action Game for Annotating Ad Video Content

                Recommendations

                Comments

                Login options

                Check if you have access through your login credentials or your institution to get full access on this article.

                Sign in
                • Published in

                  cover image ACM Other conferences
                  EANN '15: Proceedings of the 16th International Conference on Engineering Applications of Neural Networks (INNS)
                  September 2015
                  266 pages
                  ISBN:9781450335805
                  DOI:10.1145/2797143

                  Copyright © 2015 ACM

                  Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

                  Publisher

                  Association for Computing Machinery

                  New York, NY, United States

                  Publication History

                  • Published: 25 September 2015

                  Permissions

                  Request permissions about this article.

                  Request Permissions

                  Check for updates

                  Qualifiers

                  • research-article
                  • Research
                  • Refereed limited

                  Acceptance Rates

                  EANN '15 Paper Acceptance Rate36of60submissions,60%Overall Acceptance Rate36of60submissions,60%
                • Article Metrics

                  • Downloads (Last 12 months)0
                  • Downloads (Last 6 weeks)0

                  Other Metrics

                PDF Format

                View or Download as a PDF file.

                PDF

                eReader

                View online with eReader.

                eReader