Identifying sentiment of hookah-related posts on twitter

JMIR Public Health and Surveillance

Volumn 3, Issue 4, 2017, Pages

  Allem, Jon Patrick ^a   Ramanujam, Jagannathan ^a   Lerman, Kristina ^b   Chu, Kar Hai ^c   Cruz, Tess Boley ^a   Unger, Jennifer B ^a  

^a UNIVERSITY OF SOUTHERN CALIFORNIA   (United States)

^b UNIVERSITY OF SOUTHERN CALIFORNIA   (United States)

^c UNIVERSITY OF PITTSBURGH   (United States)

Author keywords

Big data; Bots; Hookah; Sentiment; Social media; Twitter; Waterpipe

Indexed keywords

EID: 85049016142     PISSN: None     EISSN: 23692960     Source Type: Journal    
DOI: 10.2196/publichealth.8133     Document Type: Article

References (28)

1. Salloum RG, Asfar T, Maziak W. Toward a Regulatory Framework for the Waterpipe. Am J Public Health 2016;106(10):1773-1777. [doi: 10.2105/AJPH.2016.303322] [Medline: 27552262]
2. Maziak W. The global epidemic of waterpipe smoking. Addict Behav 2011;36(1-2):1-5 [FREE Full text] [doi: 10.1016/j.addbeh.2010.08.030] [Medline: 20888700]
3. El-Zaatari ZM, Chami HA, Zaatari GS. Health effects associated with waterpipe smoking. Tob Control 2015;24 Suppl 1:i31-i43 [FREE Full text] [doi: 10.1136/tobaccocontrol-2014-051908] [Medline: 25661414]
4. Heinz AJ, Giedgowd GE, Crane NA, Veilleux JC, Conrad M, Braun AR, et al. A comprehensive examination of hookah smoking in college students: use patterns and contexts, social norms and attitudes, harm perception, psychological correlates and co-occurring substance use. Addict Behav 2013;38(11):2751-2760. [doi: 10.1016/j.addbeh.2013.07.009] [Medline: 23934006]
5. Primack BA, Hopkins M, Hallett C, Carroll MV, Zeller M, Dachille K, et al. US health policy related to hookah tobacco smoking. Am J Public Health 2012;102(9):e47-e51 [FREE Full text] [doi: 10.2105/AJPH.2012.300838] [Medline: 22827447]
6. Eysenbach G. Infodemiology and infoveillance tracking online health information and cyberbehavior for public health. Am J Prev Med 2011;40(5 Suppl 2):S154-S158. [doi: 10.1016/j.amepre.2011.02.006] [Medline: 21521589]
7. Ayers JW, Althouse BM, Dredze M. Could behavioral medicine lead the web data revolution? JAMA 2014;311(14):1399-1400. [doi: 10.1001/jama.2014.1505] [Medline: 24577162]
8. Allem J, Chu K, Cruz TB, Unger JB. Waterpipe Promotion and Use on Instagram: #Hookah. Nicotine Tob Res 2017;19(10):1248-1252. [doi: 10.1093/ntr/ntw329] [Medline: 28077449]
9. Krauss MJ, Sowles SJ, Moreno M, Zewdie K, Grucza RA, Bierut LJ, et al. Hookah-Related Twitter Chatter: A Content Analysis. Prev Chronic Dis 2015;12:E121 [FREE Full text] [doi: 10.5888/pcd12.150140] [Medline: 26226068]
10. Grant A, O'Mahoney H. Portrayal of waterpipe (shisha, hookah, nargile) smoking on Twitter: a qualitative exploration. Public Health 2016;140:128-135. [doi: 10.1016/j.puhe.2016.07.007] [Medline: 27520707]
11. Myslín M, Zhu S, Chapman W, Conway M. Using twitter to examine smoking behavior and perceptions of emerging tobacco products. J Med Internet Res 2013;15(8):e174 [FREE Full text] [doi: 10.2196/jmir.2534] [Medline: 23989137]
12. Davis CA, Varol O, Ferrara E, Flammini A, Menczer F. Botornot: A system to evaluate social bots. 2016 Presented at: Proceedings of the 25th International Conference Companion on World Wide Web; 2016; Montreal Canada p. 273-274.
13. Ferrara E, Varol O, Davis C, Menczer F, Flammini A. The rise of social bots. Commun ACM 2016;59(7):96-104. [doi: 10.1145/2818717]
14. Allem J, Ferrara E. The Importance of Debiasing Social Media Data to Better Understand E-Cigarette-Related Attitudes and Behaviors. J Med Internet Res 2016;18(8):e219 [FREE Full text] [doi: 10.2196/jmir.6185] [Medline: 27507563]
15. Primack B, Carroll M, Shensa A, Davis W, Levine M. Sex differences in hookah-related images posted on tumblr: a content analysis. J Health Commun 2016;21(3):366-375.
16. Chu Z, Gianvecchio S, Wang H, Jajodia S. Detecting Automation of Twitter Accounts: Are You a Human, Bot, or Cyborg? IEEE Transactions on Dependable and Secure Computing 2012;9(6):811-824. [doi: 10.1109/TCBB.2015.2462370] [Medline: 27295638]
17. Hutto C, Gilbert E. VADER: A Parsimonious Rule-based Model for Sentiment Analysis of Social Media Text. 2015 Presented at: Proceedings of the Eighth International AAAI Conference on Weblogs and Social Media, ICWSM; 2014; Ann Arbor, MI p. A.
18. Mohammad S, Kiritchenko S, Sobhani P, Zhu X, Cherry C. Detecting Stance in Tweets using Support Vector Machines. 2016 Presented at: Proceedings of SemEval-2016; June 16-17, 2016; San Diego, California.
19. Gou L, Zhou M, Yang H. KnowMeShareMe: understanding automatically discovered personality traits from social mediauser sharing preferences. 2014 Apr 06 Presented at: InProceedings of the 32nd annual ACM conference on Human factors in computing systems (pp.). ACM; 2014 Apr 26; Toronto, Ontario, Canada p. 955-964.
20. Mohammad S. #Emotional tweets. 2012 Presented at: First Joint Conference on Lexical and Computational Semantics (SEM); June 7, 2012; Montreal, Canada p. 246-255.
21. Porter M. An algorithm for suffix stripping. Program 1980;14(3):130-137.
22. Manning CD, Surdeanu M, Bauer J, Finkel J, Bethard SJ, McClosky D. The Stanford CoreNLP Natural Language Processing Toolkit. 2014 Presented at: Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics; June 22, 2014; Baltimore, Maryland p. 55-60.
23. Russell J. A circumplex model of affect. J Pers Soc Psychol 1980;39:1161-1178.
24. Bradley M, Lang P. NIMH Center for the Study of Emotion and Attention. Affective norms for English words (ANEW): Instruction manual and affective ratings. Technical report C-1, the center for research in psychophysiology, University of Florida; 1999.
25. Pechmann C, Pan L, Delucchi K, Lakon CM, Prochaska JJ. Development of a Twitter-based intervention for smoking cessation that encourages high-quality social media interactions via automessages. J Med Internet Res 2015;17(2):e50 [FREE Full text] [doi: 10.2196/jmir.3772] [Medline: 25707037]
26. Pechmann C, Delucchi K, Lakon C, Prochaska JJ. Randomised controlled trial evaluation of Tweet2Quit: a social network quit-smoking intervention. Tob Control 2017;26(2):188-194. [Medline: 26928205]
27. Allem JP, Escobedo P, Chu K, Soto DW, Cruz TB, Unger JB. Campaigns and counter campaigns: reactions on Twitter to e-cigarette education. Tob Control 2017;26(2):226-229. [doi: 10.1136/tobaccocontrol-2015-052757] [Medline: 26956467]
28. Naslund JA, Kim SJ, Aschbrenner KA, McCulloch LJ, Brunette MF, Dallery J, et al. Systematic review of social media interventions for smoking cessation. Addict Behav 2017;73:81-93. [doi: 10.1016/j.addbeh.2017.05.002] [Medline: 28499259]