Smoking is one of the leading causes of preventable death, being responsible for about six million deaths annually worldwide. Most smokers want to quit, but many find quitting difficult. The Internet enables people interested in quitting smoking to connect with others via online communities; however, the characteristics of these discussions are not well understood. This work aims to explore the textual cues of an online community interested in quitting smoking: www.reddit.com/r/ stopsmoking – “a place for redditors to motivate each other to quit smoking”. A total of approximately 5, 000 posts were randomly selected from the community. Four subgroups of posts based on the cessation days of abstainers were defined: S0: within the first week, S1: within the first month (excluding cohort S0), S2: from second month to one year, and S3: beyond one year. Psycho-linguistic features and content topics were extracted from the posts and analysed. Machine learning techniques were used to discriminate the online conversations in the first week S0 from the other subgroups. Topics and psycho-linguistic features were found to be highly valid predictors of the subgroups, possibly providing an important step in understanding social media and its use in studies of smoking and other addictions in online settings.
History
Volume
LNCS 10042
Pagination
146-153
Location
Shanghai, China
Start date
2016-11-07
End date
2016-11-10
ISSN
0302-9743
eISSN
1611-3349
ISBN-13
9783319487427
Language
eng
Publication classification
E Conference publication, E1 Full written paper - refereed
Copyright notice
2016, Springer International Publishing AG
Editor/Contributor(s)
Cellary W, Mokbel MF, Wang J, Wang H, Zhou R, Zhang Y
Title of proceedings
WISE 2016 : Proceedings of the 17th International Conference on Web Information Systems Engineering