A twitter recruitment intelligent system: association rule mining for smoking cessation

Hamed, Ahmed Abdeen; Wu, Xindong; Rubin, Alan

doi:10.1007/s13278-014-0212-6

Cited by 14 publications

(11 citation statements)

References 28 publications

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“…However, at the time when this study was undertaken, only 8 % of internet users aged 12-17 years used Twitter and thus was not a high value avenue for recruitment [14]. Still another possible avenue is the use of data-mining algorithms and machine learning for the recruitment of participants on social media sites [9]. Larger studies need to be undertaken to compare the relative effectiveness of various social media and web and/or mobile approaches for recruiting with consideration of racial, age, and gender groups of interest.…”

Section: Discussionmentioning

confidence: 99%

Recruitment of adolescents for a smoking study: use of traditional strategies and social media

Rait

Prochaska

Rubinstein

2015

Behav. Med. Pract. Policy Res.

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Engaging and retaining adolescents in research studies is challenging. Social media offers utility for expanding the sphere of research recruitment. This study examined and compared traditional and Facebook-based recruitment strategies on reach, enrollment, cost, and retention. Substance users aged 13-17 years were recruited through several methods, including social media, a study website, fliers, talks in schools, bus ads, and referrals. Study involvement included a one-time visit and semiannual follow-up surveys. 1265 individuals contacted study personnel; 629 were ineligible; 129 declined; and 200 participants enrolled. Facebook drew the greatest volume but had a high rate of ineligibles. Referrals were the most successful and cost-effective ($7 per enrolled participant); school talks were the least. Recruitment source was unrelated to retention success. Facebook may expand recruitment reach, but had greater financial costs and more ineligible contacts, resulting in fewer enrollees relative to traditional interpersonal recruitment methods. Referrals, though useful for study engagement, did not provide a differential benefit in terms of long-term retention.

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Section: Discussionmentioning

confidence: 99%

Recruitment of adolescents for a smoking study: use of traditional strategies and social media

Rait

Prochaska

Rubinstein

2015

Behav. Med. Pract. Policy Res.

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“…Large spectrums of domains are using this data, some of which are using it for academic research and others for applications [55]. New improvements regarding twitter data are presented by this section.…”

Section: Text Mining In Twittermentioning

confidence: 99%

“…Researchers of [55] demonstrated in a smoking cessation nicotine patch study an innovative Twitter recruitment system that is deployed by the group. The study aimed to describe the methodology and used to address the issue of digital recruitment.…”

Section: Text Mining In Twittermentioning

confidence: 99%

A Survey of Text Mining in Social Media: Facebook and Twitter Perspectives

Salloum¹,

Al-Emran²,

Monem³

et al. 2017

Adv. sci. technol. eng. syst. j.

176

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“…There are endless types and forms of hashtags (Hamed et al, 2014). While a hashtag can be made of a single word (e.g.…”

Section: Gtn Vs K-h Pagerank Network Analysismentioning

confidence: 99%

Measuring climate change on Twitter using Google’s algorithm: perception and events

Hamed

Ayer

Clark

et al. 2015

International Journal of Web Information Systems

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If you would like to write for this, or any other Emerald publication, then please use our Emerald for Authors service information about how to choose which publication to write for and submission guidelines are available for all. Please visit www.emeraldinsight.com/authors for more information. About Emerald www.emeraldinsight.comEmerald is a global publisher linking research and practice to the benefit of society. The company manages a portfolio of more than 290 journals and over 2,350 books and book series volumes, as well as providing an extensive range of online products and additional customer resources and services.Emerald is both COUNTER 4 and TRANSFER compliant. The organization is a partner of the Committee on Publication Ethics (COPE) and also works with Portico and the LOCKSS initiative for digital archive preservation. AbstractPurpose -The purpose of this paper is to test the hypothesis of whether more complex and emergent hashtags can be sufficient pointers to climate change events. Human-induced climate change is one of this century's greatest unbalancing forces to have affected our planet. Capturing the public awareness of climate change on Twitter has proven to be significant. In a previous research, it was demonstrated by the authors that public awareness is prominently expressed in the form of hashtags that uses more than one bigram (i.e. a climate change term). The research finding showed that this awareness is expressed by more complex terms (e.g. "climate change"). It was learned that the awareness was dominantly expressed using the hashtag: #ClimateChange. Design/methodology/approach -The methods demonstrated here use objective computational approaches [i.e. Google's ranking algorithm and Information Retrieval measures (e.g. TFIDF)] to detect and rank the emerging events. Findings -The results shows a clear significant evidence for the events signaled using emergent hashtags and how globally influential they are. The research detected the Earth Day, 2015, which was signaled using the hashtag #EarthDay. Clearly, this is a day that is globally observed by the worldwide population. Originality/value -It was proven that these computational methods eliminate the subjectivity errors associated with humans and provide inexpensive solution for event detection on Twitter. Indeed, the approach used here can also be applicable to other types of event detections, beyond climate change, and surely applicable to other social media platforms that support the use of hashtags (e.g. Facebook). The paper explains, in great detail, the methods and all the numerous events detected.

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A twitter recruitment intelligent system: association rule mining for smoking cessation

Cited by 14 publications

References 28 publications

Recruitment of adolescents for a smoking study: use of traditional strategies and social media

Recruitment of adolescents for a smoking study: use of traditional strategies and social media

A Survey of Text Mining in Social Media: Facebook and Twitter Perspectives

Measuring climate change on Twitter using Google’s algorithm: perception and events

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