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Finding Healthcare Issues with Search Engine Queries and Social Network Data

Author

Listed:
  • M. Ikram Ullah Lali

    (Department of Computer Science & IT, University of Sargodha, Sargodha, Pakistan)

  • Raza Ul Mustafa

    (Department of Computer Science, COMSATS Institute of Information Technology, Sahiwal, Pakistan)

  • Kashif Saleem

    (Centre of Excellence in Information Assurance (CoEIA), King Saud University, Riyadh, Saudi Arabia)

  • M. Saqib Nawaz

    (Department of Information Science, School of Mathematical Sciences, Peking University, Beijing, China)

  • Tehseen Zia

    (Department of Computer Science, COMSATS Institute of Information Technology, Islamabad, Pakistan)

  • Basit Shahzad

    (College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia)

Abstract

Search engines and social networks are two entirely different data sources that can provide valuable information about Influenza. While search engine hosts can deliver popular queries (or terms) used for searching the Influenza related information, the social networks contain useful links of information sources that people have found valuable. The authors hypothesize that such data sources can provide vital first-hand information. In this article, they have proposed a methodology for detecting the information sources from social networks, particularly Twitter. The data filtering and source finding tasks are posed as classification tasks. Search engine queries are used for extracting related dataset. Results have shown that propose approach can be beneficial for extracting useful information regarding side effects, medications and to track geographical location of epidemics affected area.

Suggested Citation

  • M. Ikram Ullah Lali & Raza Ul Mustafa & Kashif Saleem & M. Saqib Nawaz & Tehseen Zia & Basit Shahzad, 2017. "Finding Healthcare Issues with Search Engine Queries and Social Network Data," International Journal on Semantic Web and Information Systems (IJSWIS), IGI Global, vol. 13(1), pages 48-62, January.
    • Handle: RePEc:igg:jswis0:v:13:y:2017:i:1:p:48-62
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    Cited by:

    1. Basit Shahzad & Fazal-e-Amin & Ahsanullah Abro & Muhammad Imran & Muhammad Shoaib, 2021. "Resource Optimization-Based Software Risk Reduction Model for Large-Scale Application Development," Sustainability, MDPI, vol. 13(5), pages 1-17, March.

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