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Measuring the value of health query translation: An analysis by user language proficiency

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  • Carla Teixeira Lopes
  • Cristina Ribeiro

Abstract

English is by far the most used language on the web. In some domains, the existence of less content in the users' native language may not be problematic and even help to cope with the information overload. Yet, in domains such as health, where information quality is critical, a larger quantity of information may mean easier access to higher quality content. Query translation may be a good strategy to access content in other languages, but the presence of medical terms in health queries makes the translation process more difficult, even for users with very good language proficiencies. In this study, we evaluate how translating a health query affects users with different language proficiencies. We chose English as the non‐native language because it is a widely spoken language and it is the most used language on the web. Our findings suggest that non‐English–speaking users having at least elementary English proficiency can benefit from a system that suggests English alternatives for their queries, or automatically retrieves English content from a non‐English query. This awareness of the user profile results in higher precision, more accurate medical knowledge, and better access to high‐quality content. Moreover, the suggestions of English‐translated queries may also trigger new health search strategies.

Suggested Citation

  • Carla Teixeira Lopes & Cristina Ribeiro, 2013. "Measuring the value of health query translation: An analysis by user language proficiency," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 64(5), pages 951-963, May.
  • Handle: RePEc:bla:jamist:v:64:y:2013:i:5:p:951-963
    DOI: 10.1002/asi.22812
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    Cited by:

    1. Ben Steichen & Ryan Lowe, 2021. "How do multilingual users search? An investigation of query and result list language choices," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 72(6), pages 759-776, June.

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