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Journal of Diabetology | Volume 3
May 16-17, 2019 | Prague, Czech Republic
Diabetes and Endocrinology
27
th
International Conference on
J Diabetol, Volume 3
A novel theory of support constructs in social media discourse (SSMD) through a
study of an online Facebook Diabetes community
Bazil Stanley Solomon, Nigel Crook, Alon Lischinsky
and
Kenneth Boness
Oxford Brookes University, United Kingdom
T
his study aims to inform the way that people are directly
affected by various issues and conditions, and how they
can support each other on social media by exploring their
utilization of salient advice with stance-taking linguistic
features for chronic illness support. The study develops a
novel theory of support constructs in social media discourse.
The study makes a methodological contribution that seeks to
combine corpus linguistics (CL) with Artificial Intelligence (AI)
computational analyses and qualitative linguistic discourse
analysis to a large-scale dataset of over 200,000, anonymized
FacebookDiabetesUKposts and16,137anonymous diabetes-
related users of the platform. An adapted anonymization
process is used on the data to meet the ongoing challenges
of online ethical research requirements. People living with
diabetes are found to employ patterns of ‘topics’ and advice,
with stance-taking in their support of themselves and each
other. They tend to support each other during chronic illness
with a language pattern that includes purpose, context and
content discourse devices. These are in a broader context
of power and solidarity, demonstrating social relations
concerningriskandtrust.Hence,theuncertaintyandvariation
of effect displayedwhen sharing information for support. Log-
likelihood, precision measures and a multi-method approach
help to confirm the trends.
The implications of the new theory are aimed at healthcare
communicators towork with organizations to help their social
media users support each other by understanding a peer-
focused view of chronic illness support. Corpus linguistics
may benefit from the use of combined AI and DA approaches
to anonymized large-scale online data. This study also offers
preliminary work for support-bots to be programmed to
utilize the language patterns to automatically support people
who need them. The bots may be able to have conversations
instantaneously with many people, but to do so in natural
ways.
e
:
bazil.solomon-2011@brookes.ac.uk