The University of Southampton
University of Southampton Institutional Repository

Automatic extraction of personal experiences from patients' blogs: A case study in chronic obstructive pulmonary disease

Automatic extraction of personal experiences from patients' blogs: A case study in chronic obstructive pulmonary disease
Automatic extraction of personal experiences from patients' blogs: A case study in chronic obstructive pulmonary disease
People with long-term illness such as chronic obstructive pulmonary disease (COPD) often use social media to document and share information, opinions and their experiences with others. Analysing the self-reported experiences of patients shared online has the potential to help medical researchers gain insight into some of the key issues affecting patients. However, the scale of health conversation taking place online poses considerable challenges to traditional content analysis. In this paper, we present a system which automates extraction of patient statements which refer to a personal experience. We applied a crowdsourcing methodology to create a set of 1770 annotated sentences from blog posts written by COPD patients. Our machine learning approach trained on lexical features successfully extracted sentences about patient experience with 93% precision and 80% recall (F-measure: 86. Automatic annotation of sentences about patient experience can facilitate subsequent content analysis by highlighting the most relevant sentences to this particular problem.
Greenwood, Mark
6dcd2b83-1ae7-4c3e-85bc-d86b6cd4f2e8
Elwyn, Glyn
dd0ada9e-9b87-4734-9f9c-9a914d5e200a
Francis, Nicholas Andrew
9b610883-605c-4fee-871d-defaa86ccf8e
Preece, Alun David
7cf27e21-8fa9-4027-b7b8-0a651fbfd790
Spasic, Irena
1d0c7300-22e0-44c1-bbb1-ccb634932661
Greenwood, Mark
6dcd2b83-1ae7-4c3e-85bc-d86b6cd4f2e8
Elwyn, Glyn
dd0ada9e-9b87-4734-9f9c-9a914d5e200a
Francis, Nicholas Andrew
9b610883-605c-4fee-871d-defaa86ccf8e
Preece, Alun David
7cf27e21-8fa9-4027-b7b8-0a651fbfd790
Spasic, Irena
1d0c7300-22e0-44c1-bbb1-ccb634932661

Greenwood, Mark, Elwyn, Glyn, Francis, Nicholas Andrew, Preece, Alun David and Spasic, Irena (2013) Automatic extraction of personal experiences from patients' blogs: A case study in chronic obstructive pulmonary disease. Third International Conference on Social Computing and its Applications, , Karlsruhe, Germany. 30 Sep - 02 Oct 2013.

Record type: Conference or Workshop Item (Paper)

Abstract

People with long-term illness such as chronic obstructive pulmonary disease (COPD) often use social media to document and share information, opinions and their experiences with others. Analysing the self-reported experiences of patients shared online has the potential to help medical researchers gain insight into some of the key issues affecting patients. However, the scale of health conversation taking place online poses considerable challenges to traditional content analysis. In this paper, we present a system which automates extraction of patient statements which refer to a personal experience. We applied a crowdsourcing methodology to create a set of 1770 annotated sentences from blog posts written by COPD patients. Our machine learning approach trained on lexical features successfully extracted sentences about patient experience with 93% precision and 80% recall (F-measure: 86. Automatic annotation of sentences about patient experience can facilitate subsequent content analysis by highlighting the most relevant sentences to this particular problem.

This record has no associated files available for download.

More information

Published date: 1 September 2013
Venue - Dates: Third International Conference on Social Computing and its Applications, , Karlsruhe, Germany, 2013-09-30 - 2013-10-02

Identifiers

Local EPrints ID: 436302
URI: http://eprints.soton.ac.uk/id/eprint/436302
PURE UUID: c2d72603-751b-4af6-9553-089790af3a37
ORCID for Nicholas Andrew Francis: ORCID iD orcid.org/0000-0001-8939-7312

Catalogue record

Date deposited: 06 Dec 2019 17:30
Last modified: 08 Jan 2022 03:40

Export record

Contributors

Author: Mark Greenwood
Author: Glyn Elwyn
Author: Alun David Preece
Author: Irena Spasic

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×