Literature DB >> 25438614

Behavioral insights on big data: using social media for predicting biomedical outcomes.

Sean D Young1.   

Abstract

Social media 'big data' can provide valuable insights about people's behaviors, such as their likelihood of engaging in risk behaviors or contracting a disease. Although in its infancy, advancing this research provides the promise of predicting health-related behaviors to promptly prepare for and respond to public health emergencies and epidemics.
Copyright © 2014 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  behavioral insights; big data; prediction; social media

Mesh：

Year:  2014        PMID： 25438614      PMCID： PMC4364914          DOI： 10.1016/j.tim.2014.08.004

Source DB:  PubMed          Journal:  Trends Microbiol        ISSN： 0966-842X            Impact factor:   17.079


  9 in total

1.  Biology: The big challenges of big data.

Authors:  Vivien Marx
Journal:  Nature       Date:  2013-06-13       Impact factor: 49.962

2.  The inevitable application of big data to health care.

Authors:  Travis B Murdoch; Allan S Detsky
Journal:  JAMA       Date:  2013-04-03       Impact factor: 56.272

3.  Big data. The parable of Google Flu: traps in big data analysis.

Authors:  David Lazer; Ryan Kennedy; Gary King; Alessandro Vespignani
Journal:  Science       Date:  2014-03-14       Impact factor: 47.728

4.  Pandemics in the age of Twitter: content analysis of Tweets during the 2009 H1N1 outbreak.

Authors:  Cynthia Chew; Gunther Eysenbach
Journal:  PLoS One       Date:  2010-11-29       Impact factor: 3.240

5.  Online social networking for HIV education and prevention: a mixed-methods analysis.

Authors:  Sean D Young; Devan Jaganath
Journal:  Sex Transm Dis       Date:  2013-02       Impact factor: 2.830

6.  Methods of using real-time social media technologies for detection and remote monitoring of HIV outcomes.

Authors:  Sean D Young; Caitlin Rivers; Bryan Lewis
Journal:  Prev Med       Date:  2014-02-08       Impact factor: 4.018

7.  Extrapolating psychological insights from Facebook profiles: a study of religion and relationship status.

Authors:  Sean Young; Debo Dutta; Gopal Dommety
Journal:  Cyberpsychol Behav       Date:  2009-06

8.  Using twitter to examine smoking behavior and perceptions of emerging tobacco products.

Authors:  Mark Myslín; Shu-Hong Zhu; Wendy Chapman; Mike Conway
Journal:  J Med Internet Res       Date:  2013-08-29       Impact factor: 5.428

9.  National and local influenza surveillance through Twitter: an analysis of the 2012-2013 influenza epidemic.

Authors:  David A Broniatowski; Michael J Paul; Mark Dredze
Journal:  PLoS One       Date:  2013-12-09       Impact factor: 3.240
  9 in total
  16 in total

1.  Symptom clusters in women with breast cancer: an analysis of data from social media and a research study.

Authors:  Sarah A Marshall; Christopher C Yang; Qing Ping; Mengnan Zhao; Nancy E Avis; Edward H Ip
Journal:  Qual Life Res       Date:  2015-10-17       Impact factor: 4.147

2.  An Online Risk Index for the Cross-Sectional Prediction of New HIV Chlamydia, and Gonorrhea Diagnoses Across U.S. Counties and Across Years.

Authors:  Man-Pui Sally Chan; Sophie Lohmann; Alex Morales; Chengxiang Zhai; Lyle Ungar; David R Holtgrave; Dolores Albarracín
Journal:  AIDS Behav       Date:  2018-07

3.  Toward Automating HIV Identification: Machine Learning for Rapid Identification of HIV-Related Social Media Data.

Authors:  Sean D Young; Wenchao Yu; Wei Wang
Journal:  J Acquir Immune Defic Syndr       Date:  2017-02-01       Impact factor: 3.731

4.  Mining the social mediome.

Authors:  David A Asch; Daniel J Rader; Raina M Merchant
Journal:  Trends Mol Med       Date:  2015-09       Impact factor: 11.951

5.  Sexual Self-Schemas in the Real World: Investigating the Ecological Validity of Language-Based Markers of Childhood Sexual Abuse.

Authors:  Amelia M Stanton; Cindy M Meston; Ryan L Boyd
Journal:  Cyberpsychol Behav Soc Netw       Date:  2017-06-01

6.  A Collaborative Approach to Identifying Social Media Markers of Schizophrenia by Employing Machine Learning and Clinical Appraisals.

Authors:  Michael L Birnbaum; Sindhu Kiranmai Ernala; Asra F Rizvi; Munmun De Choudhury; John M Kane
Journal:  J Med Internet Res       Date:  2017-08-14       Impact factor: 5.428

7.  HIV-related posts from a Chinese internet discussion forum: An exploratory study.

Authors:  Yuan Dong; Xin Zhou; Yi Lin; Qichao Pan; Ying Wang
Journal:  PLoS One       Date:  2019-02-28       Impact factor: 3.240

8.  Social Big Data as a Tool for Understanding and Predicting the Impact of Cannabis Legalization.

Authors:  Sean D Young; Howard Padwa; Erin E Bonar
Journal:  Front Public Health       Date:  2019-10-04

9.  Social Media as a New Vital Sign: Commentary.

Authors:  Sean D Young
Journal:  J Med Internet Res       Date:  2018-04-30       Impact factor: 5.428

10.  Mental Health-Related Behaviors and Discussions Among Young Adults: Analysis and Classification.

Authors:  Ryan Rivas; Moloud Shahbazi; Renee Garett; Vagelis Hristidis; Sean Young
Journal:  J Med Internet Res       Date:  2020-05-29       Impact factor: 5.428
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