Extracting key challenges in achieving sobriety through shared subspace learning

Harikumar, Haripriya, Nguyen, Thin, Rana, Santu, Gupta, Sunil, Kaimal, Ramachandra and Venkatesh, Svetha 2016, Extracting key challenges in achieving sobriety through shared subspace learning, in ADMA 2016 : Proceedings of the 12th Advanced Data Mining and Applications International Conference, Springer International, Cham, Switzerland, pp. 420-433, doi: 10.1007/978-3-319-49586-6_28.

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Title Extracting key challenges in achieving sobriety through shared subspace learning
Author(s) Harikumar, Haripriya
Nguyen, ThinORCID iD for Nguyen, Thin orcid.org/0000-0003-3467-8963
Rana, SantuORCID iD for Rana, Santu orcid.org/0000-0003-2247-850X
Gupta, SunilORCID iD for Gupta, Sunil orcid.org/0000-0002-3308-1930
Kaimal, Ramachandra
Venkatesh, SvethaORCID iD for Venkatesh, Svetha orcid.org/0000-0001-8675-6631
Conference name Advanced Data Mining and Applications. International Conference (12th : 2016 : Gold Coast, Queensland)
Conference location Gold Coast, Queensland
Conference dates 12-15 Dec. 2016
Title of proceedings ADMA 2016 : Proceedings of the 12th Advanced Data Mining and Applications International Conference
Editor(s) Li, Jinyan
Li, Xue
Wang, Shuliang
Li, Jianxin
Sheng, Quan Z.
Publication date 2016
Series Lecture notes in artificial intelligence
Conference series Advanced Data Mining and Applications International Conference
Start page 420
End page 433
Total pages 14
Publisher Springer International
Place of publication Cham, Switzerland
Keyword(s) social media
shared subspace
alcohol addiction
Summary Alcohol abuse is quite common among all people without any age restrictions. The uncontrolled use of alcohol affects both the individual and society. Alcohol addiction leads to a huge increase in crime, suicide, health related problems and financial crisis. Research has shown that certain behavioral changes can be effective towards staying abstained. The analysis of behavioral changes of quitters and those who are at the beginning phase of quitting can be useful for reducing the issues related to alcohol addiction. Most of the conventional approaches are based on surveys and, therefore, expensive in both time and cost. Social media has lend itself as a source of large, diverse and unbiased data for analyzing social behaviors. Reddit is a social media platform where a large number of people communicate with each other. It has many different sub-groups called subreddits categorized based on the subject. We collected more than 40,000 self reported user’s data from a subreddit called ‘/r/stopdrinking’. We divide the data into two groups, short-term with abstinent days less than 30 and long-term abstainers with abstinent days greater than 365 based on badge days at the time of post submission. Common and discriminative topics are extracted from the data using JS-NMF, a shared subspace non-negative matrix factorization method. The validity of the extracted topics are demonstrated through predictive performance.
ISBN 9783319495859
ISSN 0302-9743
Language eng
DOI 10.1007/978-3-319-49586-6_28
Field of Research 080109 Pattern Recognition and Data Mining
Socio Economic Objective 0 Not Applicable
HERDC Research category E1 Full written paper - refereed
ERA Research output type E Conference publication
Copyright notice ©2016, Springer International Publishing
Persistent URL http://hdl.handle.net/10536/DRO/DU:30093592

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