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Drug Safety

, Volume 40, Issue 2, pp 187–188 | Cite as

Authors’ Reply to Jouanjus and Colleagues’ Comment on “Social Media Mining for Toxicovigilance: Automatic Monitoring of Prescription Medication Abuse from Twitter”

  • Abeed Sarker
  • Dan Malone
  • Graciela Gonzalez
Letter to the Editor

Keywords

Social Media Natural Language Processing Social Media Data Supervise Learning Technique Automate Monitoring System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Compliance with Ethical Standards

Funding

No sources of funding were used to assist in the preparation of this authors’ response.

Conflict of interest

Abeed Sarker, Dan Malone, and Graciela Gonzalez have no conflicts of interest that are directly relevant to the content of this authors’ response.

Ethics approval

Not applicable.

Informed consent

Not applicable.

References

  1. 1.
    Jouanjus E, Mallaret M, Micallef J, et al. Comment on ‘Social media mining for toxicovigilance: monitoring prescription medication abuse from Twitter. Drug Saf. 2017. doi:  10.1007/s40264-016-0497-7
  2. 2.
    Sarker A, O’Connor K, Ginn R, et al. Social media mining for toxicovigilance: automatic monitoring of prescription medication abuse from Twitter. Drug Saf. 2016;39(3):231–40.CrossRefPubMedPubMedCentralGoogle Scholar
  3. 3.
    Jouanjus E, Pourcel L, Saivin S, et al. Use of multiple sources and capture-recapture method to estimate the frequency of hospitalizations related to drug abuse. Pharmacoepidemiol Drug Saf. 2012;21(7):733–41.CrossRefPubMedGoogle Scholar
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    Manasco AT, Griggs C, Leeds R, et al. Characteristics of state prescription drug monitoring programs: a state-by-state survey. Pharmacoepidemiol Drug Saf. 2016;25(7):847–51.CrossRefPubMedGoogle Scholar
  5. 5.
    Sarker A, Ginn R, Nikfarjam A, et al. Utilizing social media data for pharmacovigilance: a review. J Biomed Inform. 2015;54:202–12.CrossRefPubMedPubMedCentralGoogle Scholar
  6. 6.
    Paul MJ, Sarker A, Brownstein JS, et al. Social media mining for public health monitoring and surveillance. Pac Symp Biocomput. 2016;21:468–79.Google Scholar
  7. 7.
    Sarker A, Gonzalez G. A corpus for mining drug-related knowledge from Twitter chatter: language models and their utilities. Data Brief. 2016;10:122–31.CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2017

Authors and Affiliations

  1. 1.Division of Informatics, Department of Biostatistics and Epidemiology, Perelman School of MedicineUniversity of PennsylvaniaPhiladelphiaUSA
  2. 2.Department of Pharmacy Practice and ScienceUniversity of ArizonaTucsonUSA

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