Machine intelligence for health information

Capturing concepts and trends in social media via query expansion

Xing Yu Su, Hanna Suominen, Leif Hanlen

Research output: A Conference proceeding or a Chapter in BookConference contribution

3 Citations (Scopus)

Abstract

Introduction. We aim to improve retrieval of health information from Twitter. Background. The popularity of social media and micro-blogs has emphasised their potential for knowledge discovery and trend building. However, capturing and relating concepts in these short-spoken and lexically extensive sources of information requires search engines with increasing intelligence. Methods. Our approach uses query expansion techniques to associate query terms with the most similar Twitter terms to capture trends in the gamut of information. Results. We demonstrated the value, defined as improved precision, of our search engine by considering three search tasks and two independent annotators. We also showed the stability of the engine with an increasing number of tweets; this is crucial as large data sets are needed for capturing trends with high confidence. These results encourage us to continue developing the engine for discovering trends in health information available at Twitter.

Original languageEnglish
Title of host publicationHealth Informatics: The Transformative Power of Innovation - Selected Papers from the 19th Australian National Health Informatics Conference, HIC 2011
PublisherIOS Press
Pages150-157
Number of pages8
Volume168
ISBN (Print)9781607507901
DOIs
Publication statusPublished - 2011
Externally publishedYes
Event19th Australian National Health Informatics Conference, HIC 2011 - Brisbane, Brisbane, Australia
Duration: 1 Aug 20115 Aug 2011

Conference

Conference19th Australian National Health Informatics Conference, HIC 2011
CountryAustralia
CityBrisbane
Period1/08/115/08/11

Fingerprint

Social Media
Search Engine
Artificial Intelligence
Search engines
Blogging
Health
Engines
Blogs
Information Storage and Retrieval
Intelligence
Data mining
Datasets

Cite this

Su, X. Y., Suominen, H., & Hanlen, L. (2011). Machine intelligence for health information: Capturing concepts and trends in social media via query expansion. In Health Informatics: The Transformative Power of Innovation - Selected Papers from the 19th Australian National Health Informatics Conference, HIC 2011 (Vol. 168, pp. 150-157). IOS Press. https://doi.org/10.3233/978-1-60750-791-8-150
Su, Xing Yu ; Suominen, Hanna ; Hanlen, Leif. / Machine intelligence for health information : Capturing concepts and trends in social media via query expansion. Health Informatics: The Transformative Power of Innovation - Selected Papers from the 19th Australian National Health Informatics Conference, HIC 2011. Vol. 168 IOS Press, 2011. pp. 150-157
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abstract = "Introduction. We aim to improve retrieval of health information from Twitter. Background. The popularity of social media and micro-blogs has emphasised their potential for knowledge discovery and trend building. However, capturing and relating concepts in these short-spoken and lexically extensive sources of information requires search engines with increasing intelligence. Methods. Our approach uses query expansion techniques to associate query terms with the most similar Twitter terms to capture trends in the gamut of information. Results. We demonstrated the value, defined as improved precision, of our search engine by considering three search tasks and two independent annotators. We also showed the stability of the engine with an increasing number of tweets; this is crucial as large data sets are needed for capturing trends with high confidence. These results encourage us to continue developing the engine for discovering trends in health information available at Twitter.",
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Su, XY, Suominen, H & Hanlen, L 2011, Machine intelligence for health information: Capturing concepts and trends in social media via query expansion. in Health Informatics: The Transformative Power of Innovation - Selected Papers from the 19th Australian National Health Informatics Conference, HIC 2011. vol. 168, IOS Press, pp. 150-157, 19th Australian National Health Informatics Conference, HIC 2011, Brisbane, Australia, 1/08/11. https://doi.org/10.3233/978-1-60750-791-8-150

Machine intelligence for health information : Capturing concepts and trends in social media via query expansion. / Su, Xing Yu; Suominen, Hanna; Hanlen, Leif.

Health Informatics: The Transformative Power of Innovation - Selected Papers from the 19th Australian National Health Informatics Conference, HIC 2011. Vol. 168 IOS Press, 2011. p. 150-157.

Research output: A Conference proceeding or a Chapter in BookConference contribution

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AU - Hanlen, Leif

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N2 - Introduction. We aim to improve retrieval of health information from Twitter. Background. The popularity of social media and micro-blogs has emphasised their potential for knowledge discovery and trend building. However, capturing and relating concepts in these short-spoken and lexically extensive sources of information requires search engines with increasing intelligence. Methods. Our approach uses query expansion techniques to associate query terms with the most similar Twitter terms to capture trends in the gamut of information. Results. We demonstrated the value, defined as improved precision, of our search engine by considering three search tasks and two independent annotators. We also showed the stability of the engine with an increasing number of tweets; this is crucial as large data sets are needed for capturing trends with high confidence. These results encourage us to continue developing the engine for discovering trends in health information available at Twitter.

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Su XY, Suominen H, Hanlen L. Machine intelligence for health information: Capturing concepts and trends in social media via query expansion. In Health Informatics: The Transformative Power of Innovation - Selected Papers from the 19th Australian National Health Informatics Conference, HIC 2011. Vol. 168. IOS Press. 2011. p. 150-157 https://doi.org/10.3233/978-1-60750-791-8-150