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Improving Personal Health Mention detection on Twitter using Permutation Based Word Representation Learning

conference contribution
posted on 2020-01-01, 00:00 authored by Pervaiz Iqbal Khan, Imran RazzakImran Razzak, Andreas Dengel, Sheraz Ahmed
Social media has become a substitute for social interaction, thus the amount of medical and clinical-related information on the web is increasing. Monitoring of Personal Health Mentioning (PHM) on social media is an active area of research that predicts whether a given piece of text contains a health condition or not. To this end, the main idea is to consider the usage of disease or symptom words in the text. However, due to their usage in a figurative sense, disease or symptom words may not always indicate the presence of the health condition. Prior work attempts to address this by considering contextual word representations along with the utilization of the sentiment information. However, these methods are unable to capture the complete context in which symptom word is used. In this work, we incorporate permutation-based contextual word representation for the task of health mention detection which captures the context of disease words efficiently, in the given piece of text, and hence improves the performance of the classifier. To evaluate the integrity of the proposed method, we perform experimentation on the public benchmark dataset that shows an improvement of 5.5% in F-score in comparison to the state of the art health mention detection classifier. (Code is available at https://github.com/pervaizniazi/Figurative-Mention).

History

Volume

12532

Pagination

776-785

Location

Online : Bangkok, Thailand

Start date

2020-11-23

End date

2020-11-27

ISSN

0302-9743

eISSN

1611-3349

ISBN-13

9783030638290

Language

eng

Publication classification

E1 Full written paper - refereed

Copyright notice

2020, Springer Nature Switzerland AG

Editor/Contributor(s)

Yang H, Leung AC-S, Chan JH, Pasupa K, Kwok JT, King I

Title of proceedings

ICONIP 2020 : 27th International Conference on Neural Information Processing - Part 1

Event

ICONIP - Neural Informational Processing. International Conference (27th : 2020 : Bangkok, Thailand)

Publisher

Springer Nature

Place of publication

Cham, Switzerland

Series

Lecture Notes in Computer Science Book Series (LNCS)

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