A Twitter-based smoking cessation recruitment system

Digital recruitment is increasingly becoming a popular avenue for identifying human subjects for various studies. The process starts with an online ad that describes the task and explains expectations. As social media has exploded in popularity, efforts are being made to use social media to recruit...

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Published in:Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining : ASONAM 2013 : Niagara Falls, Canada, August 25-28, 2013 pp. 854 - 861
Main Authors: Hamed, Ahmed Abdeen, Xindong Wu, Fingar, James R.
Format: Conference Proceeding
Language:English
Published: ACM and IEEE 01.08.2013
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Abstract Digital recruitment is increasingly becoming a popular avenue for identifying human subjects for various studies. The process starts with an online ad that describes the task and explains expectations. As social media has exploded in popularity, efforts are being made to use social media to recruit for new career opportunities. Particularly, LinkedIn and Twitter have enabled an emerging trend for matching individuals with possible opportunities based on their interests. This makes finding more relevant jobs easier for both employees and employers. There are, however, many unanswered questions about how best to do that. In this paper, we propose an innovative Twitter-based recruitment system for a smoking cessation nicotine patch study. The goals of the paper are to (1) provide the system specification and design, (2) propose the approach we have taken to solve the problem of digital recruitment, (3) present two new algorithms, one for Twitter user ranking and the other for digital recruitment using social media, and (4) present the promising outcome of the initial version of the system and summarize the results. This is the first effort to introduce a practical solution for digital recruitment campaigns that is large-scale, inexpensive, efficient and reaches out to individuals in real-time as their needs are expressed. A continuous update on how our system is performing, in real-time, can be viewed at https://twitter.com/TobaccoQuit.
AbstractList Digital recruitment is increasingly becoming a popular avenue for identifying human subjects for various studies. The process starts with an online ad that describes the task and explains expectations. As social media has exploded in popularity, efforts are being made to use social media to recruit for new career opportunities. Particularly, LinkedIn and Twitter have enabled an emerging trend for matching individuals with possible opportunities based on their interests. This makes finding more relevant jobs easier for both employees and employers. There are, however, many unanswered questions about how best to do that. In this paper, we propose an innovative Twitter-based recruitment system for a smoking cessation nicotine patch study. The goals of the paper are to (1) provide the system specification and design, (2) propose the approach we have taken to solve the problem of digital recruitment, (3) present two new algorithms, one for Twitter user ranking and the other for digital recruitment using social media, and (4) present the promising outcome of the initial version of the system and summarize the results. This is the first effort to introduce a practical solution for digital recruitment campaigns that is large-scale, inexpensive, efficient and reaches out to individuals in real-time as their needs are expressed. A continuous update on how our system is performing, in real-time, can be viewed at https://twitter.com/TobaccoQuit.
Author Fingar, James R.
Xindong Wu
Hamed, Ahmed Abdeen
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  surname: Xindong Wu
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  givenname: James R.
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  fullname: Fingar, James R.
  email: james.fingar@med.uvm.edu
  organization: Dept. of Psychiatry, Univ. of Vermont, Burlington, VT, USA
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Snippet Digital recruitment is increasingly becoming a popular avenue for identifying human subjects for various studies. The process starts with an online ad that...
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SubjectTerms Algorithm design and analysis
Media
Monitoring
Real-time systems
Recruitment
Twitter
Title A Twitter-based smoking cessation recruitment system
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