Abstract
In intercultural collaboration, the lack of a common ground, typically evidenced by language differences, can result in misunderstandings. Many times, team members do not realize that a misunderstanding exists during the collaboration. One solution is to identifying the words that have a high probability of causing misunderstanding. However, it is difficult for people to identify those words, especially for monolingual and monocultural people, as they have never experienced the language and culture of the other party. Many researchers have been trying to identify cultural differences using survey studies but the resulting coverage is limited, requires excessive effort, and can yield bias. In this paper, we propose a novel method that applies an image comparison technique to an image database to automatically detect words that might cause misunderstanding. We test our method on 2,500 words in a Japanese-English concept dictionary called Japanese WordNet. This paper provides explains the results gained. We also discuss the use of the proposal and visualization as a support tool to enhance intercultural workshops.
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Acknowledgments
This research was partially supported by a Grant-in-Aid for Scientific Research (A) (17H00759, 2017–2020) and (B) (18H03341, 2018–2020) from Japan Society for the Promotion of Science (JSPS).
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Pituxcoosuvarn, M., Lin, D., Ishida, T. (2019). A Method for Automated Detection of Cultural Difference Based on Image Similarity. In: Nakanishi, H., Egi, H., Chounta, IA., Takada, H., Ichimura, S., Hoppe, U. (eds) Collaboration Technologies and Social Computing. CRIWG+CollabTech 2019. Lecture Notes in Computer Science(), vol 11677. Springer, Cham. https://doi.org/10.1007/978-3-030-28011-6_9
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