Mining Health Discussions on Suomi24

This paper discusses an effective way to fuse multiple tools to make a modern and easy-to-use software to get some key findings about health related topics on online social platforms, with a special focus on the famous Finnish forum, Suomi24. Several natural language processing have been tested and, sometimes, modified in order to accommodate the Finnish language linguistic structure and achieve our tasks of mining the health discussion content. We also explore the ability to monitor and track diseases in Finish open discussion forum. The developed modular system can help clinicians and medical experts to analyze similar forums to identify and track related events that can be correlated with hospital dataset in order to generate new hypotheses that initiate future treatment based approaches.

Authors:
Ibrahim Moamen, Eteläperä Matti, Turkmen Sercan, Maged Mina, Oussalah Mourad, Miettunen Jouko

Publication type:
A4 Article in conference proceedings

Place of publication:
2019 IEEE Intl Conf on Parallel & Distributed Processing with Applications, Big Data & Cloud Computing, Sustainable Computing & Communications, Social Computing & Networking (ISPA/BDCloud/SocialCom/SustainCom)

Keywords:
-disease-detection, natural language processing, sentiment analysis, Suomi24

Published:

Full citation:
M. Ibrahim, M. Eteläperä, S. Turkmen, M. Maged, M. Oussalah and J. Miettunen, “Mining Health Discussions on Suomi24,” 2019 IEEE Intl Conf on Parallel & Distributed Processing with Applications, Big Data & Cloud Computing, Sustainable Computing & Communications, Social Computing & Networking (ISPA/BDCloud/SocialCom/SustainCom), Xiamen, China, 2019, pp. 1580-1585.

DOI:
https://doi.org/10.1109/ISPA-BDCloud-SustainCom-SocialCom48970.2019.00232

Read the publication here:
http://urn.fi/urn:nbn:fi-fe202003319806