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Best matches for ("natural language processing" OR "text mining") "social media"[tiab]:

Combining natural language processing and network analysis to examine how advocacy organizations stimulate conversation on social media. Bail CA et al. Proc Natl Acad Sci U S A. (2016)

Natural Language Processing of Social Media as Screening for Suicide Risk. Coppersmith G et al. Biomed Inform Insights. (2018)

Advances in natural language processing. Hirschberg J et al. Science. (2015)

Search results

Items: 1 to 20 of 196

1.

Natural Language Processing of Reddit Data to Evaluate Dermatology Patient Experiences and Therapeutics.

Okon E, Rachakonda V, Hong HJ, Callison-Burch C, Lipoff J.

J Am Acad Dermatol. 2019 Jul 12. pii: S0190-9622(19)32371-0. doi: 10.1016/j.jaad.2019.07.014. [Epub ahead of print]

PMID:
31306722
2.

Identifying Key Target Audiences for Public Health Campaigns: Leveraging Machine Learning in the Case of Hookah Tobacco Smoking.

Chu KH, Colditz J, Malik M, Yates T, Primack B.

J Med Internet Res. 2019 Jul 8;21(7):e12443. doi: 10.2196/12443.

3.

Risk assessment strategies for early detection and prediction of infectious disease outbreaks associated with climate change.

Rees EE, Ng V, Gachon P, Mawudeku A, McKenney D, Pedlar J, Yemshanov D, Parmely J, Knox J.

Can Commun Dis Rep. 2019 May 2;45(5):119-126. doi: 10.14745/ccdr.v45i05a02. eCollection 2019 May 2.

4.

Detecting Signs of Depression in Tweets in Spanish: Behavioral and Linguistic Analysis.

Leis A, Ronzano F, Mayer MA, Furlong LI, Sanz F.

J Med Internet Res. 2019 Jun 27;21(6):e14199. doi: 10.2196/14199.

5.

"Baby Wants Tacos": Analysis of Health-Related Facebook Posts from Young Pregnant Women.

Marshall E, Moon MA, Mirchandani A, Smith DG, Nichols LP, Zhao X, Vydiswaran VGV, Chang T.

Matern Child Health J. 2019 Jun 20. doi: 10.1007/s10995-019-02776-7. [Epub ahead of print]

PMID:
31222598
6.

Exploring Research-Methods Blogs in Psychology: Who Posts What About Whom, and With What Effect?

Nicolas G, Bai X, Fiske ST.

Perspect Psychol Sci. 2019 Jul;14(4):691-704. doi: 10.1177/1745691619835216. Epub 2019 Jun 14.

PMID:
31199886
7.

Mining of Textual Health Information from Reddit: Analysis of Chronic Diseases With Extracted Entities and Their Relations.

Foufi V, Timakum T, Gaudet-Blavignac C, Lovis C, Song M.

J Med Internet Res. 2019 Jun 13;21(6):e12876. doi: 10.2196/12876.

8.

A natural language processing framework to analyse the opinions on HPV vaccination reflected in twitter over 10 years (2008 - 2017).

Luo X, Zimet G, Shah S.

Hum Vaccin Immunother. 2019 Jul 16:1-9. doi: 10.1080/21645515.2019.1627821. [Epub ahead of print]

PMID:
31194609
9.

Sentimental text mining based on an additional features method for text classification.

Cheng CH, Chen HH.

PLoS One. 2019 Jun 5;14(6):e0217591. doi: 10.1371/journal.pone.0217591. eCollection 2019.

10.

Identifying Key Topics Bearing Negative Sentiment on Twitter: Insights Concerning the 2015-2016 Zika Epidemic.

Mamidi R, Miller M, Banerjee T, Romine W, Sheth A.

JMIR Public Health Surveill. 2019 Jun 4;5(2):e11036. doi: 10.2196/11036.

11.

Early Detection of Adverse Drug Reactions in Social Health Networks: A Natural Language Processing Pipeline for Signal Detection.

Nikfarjam A, Ransohoff JD, Callahan A, Jones E, Loew B, Kwong BY, Sarin KY, Shah NH.

JMIR Public Health Surveill. 2019 Jun 3;5(2):e11264. doi: 10.2196/11264.

12.

Evaluating Patient Experiences in Dry Eye Disease Through Social Media Listening Research.

Cook N, Mullins A, Gautam R, Medi S, Prince C, Tyagi N, Kommineni J.

Ophthalmol Ther. 2019 Jun 3. doi: 10.1007/s40123-019-0188-4. [Epub ahead of print]

PMID:
31161531
13.

Health Information Technology Trends in Social Media: Using Twitter Data.

Lee J, Kim J, Hong YJ, Piao M, Byun A, Song H, Lee HS.

Healthc Inform Res. 2019 Apr;25(2):99-105. doi: 10.4258/hir.2019.25.2.99. Epub 2019 Apr 30.

14.

Do no harm: Natural language processing of social media supports safety of aseptic allergen immunotherapy procedures.

Press VG, Nyenhuis SM.

J Allergy Clin Immunol. 2019 Jul;144(1):38-40. doi: 10.1016/j.jaci.2019.04.022. Epub 2019 May 17. No abstract available.

PMID:
31109637
15.

Reactions to foodborne Escherichia coli outbreaks: A text-mining analysis of the public's response.

Glowacki EM, Glowacki JB, Chung AD, Wilcox GB.

Am J Infect Control. 2019 May 16. pii: S0196-6553(19)30232-9. doi: 10.1016/j.ajic.2019.04.004. [Epub ahead of print]

PMID:
31104869
16.

The Adverse Drug Reactions From Patient Reports in Social Media Project: Protocol for an Evaluation Against a Gold Standard.

Arnoux-Guenegou A, Girardeau Y, Chen X, Deldossi M, Aboukhamis R, Faviez C, Dahamna B, Karapetiantz P, Guillemin-Lanne S, Lillo-Le Louët A, Texier N, Burgun A, Katsahian S.

JMIR Res Protoc. 2019 May 7;8(5):e11448. doi: 10.2196/11448.

17.

Deep learning in ophthalmology: The technical and clinical considerations.

Ting DSW, Peng L, Varadarajan AV, Keane PA, Burlina PM, Chiang MF, Schmetterer L, Pasquale LR, Bressler NM, Webster DR, Abramoff M, Wong TY.

Prog Retin Eye Res. 2019 Apr 29. pii: S1350-9462(18)30090-9. doi: 10.1016/j.preteyeres.2019.04.003. [Epub ahead of print] Review.

PMID:
31048019
18.

Crowdbreaks: Tracking Health Trends Using Public Social Media Data and Crowdsourcing.

Müller MM, Salathé M.

Front Public Health. 2019 Apr 12;7:81. doi: 10.3389/fpubh.2019.00081. eCollection 2019.

19.

Machine Learning Methods to Predict Social Media Disaster Rumor Refuters.

Wang S, Li Z, Wang Y, Zhang Q.

Int J Environ Res Public Health. 2019 Apr 24;16(8). pii: E1452. doi: 10.3390/ijerph16081452.

20.

Profiling Commenters on Mental Health-Related Online Forums: A Methodological Example Focusing on Eating Disorder-Related Commenters.

McCaig D, Elliott MT, Siew CS, Walasek L, Meyer C.

JMIR Ment Health. 2019 Apr 22;6(4):e12555. doi: 10.2196/12555.

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