Deakin University
Browse

File(s) under permanent embargo

Understanding behavioral differences between short and long-term drinking abstainers from social media

Version 2 2024-06-05, 11:49
Version 1 2017-04-06, 12:19
conference contribution
posted on 2016-11-13, 00:00 authored by Haripriya Harikumar, Thin NguyenThin Nguyen, Sunil GuptaSunil Gupta, Santu RanaSantu Rana, R Kaimal, Svetha VenkateshSvetha Venkatesh
Drinking alcohol has high cost on society. The journey from being a regular drinker to a successful quitter may be a long and hard journey, fraught with the risk to relapse. Research has shown that certain behavioral changes can be effective towards staying abstained. Traditional way to conduct research on drinking abstainers uses questionnaire based approach to collect data from a curated group of people. However, it is an expensive approach in both cost and time and often results in small data with less diversity. Recently, social media has emerged as a rich data source. Reddit is one such social media platform that has a community (‘subreddit’) with an interest to quit drinking. The discussions among the group dates back to year 2011 and contain more than 40,000 posts. This large scale data is generated by users themselves and without being limited by any survey questionnaires. The most predictive factors from the features (unigrams, topics and LIWC) associated with short-term and long-term abstinence are identified using Lasso. It is seen that many common patterns manifest in unigrams, topics and LIWC. Whilst topics provided much richer associations between a group of words and the outcome, unigrams and LIWC are found to be good at finding highly predictive solo and psycho linguistically important words. Combining them we have found that many interesting patterns that are associated with the successful attempt made by the long-term abstainer, at the same time finding many of the common issues faced during the initial period of abstinence.

History

Event

Advanced Data Mining and Applications. International Conference (12th : 2016 : Gold Coast, Queensland)

Volume

10086

Series

Lecture notes in artificial intelligence

Pagination

520 - 533

Publisher

Springer International

Location

Gold Coast, Queensland

Place of publication

Cham, Switzerland

Start date

2016-12-12

End date

2016-12-15

ISSN

0302-9743

eISSN

1611-3349

ISBN-13

9783319495859

Language

eng

Publication classification

E Conference publication; E1 Full written paper - refereed

Copyright notice

2016, Springer International

Editor/Contributor(s)

J Li, J Li, X Li, Q Sheng, S Wang

Title of proceedings

ADMA 2016 : Proceedings of the 12th Advanced Data Mining and Applications International Conference

Usage metrics

    Research Publications

    Categories

    No categories selected

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC