[1]
|
When are alcohol-related blackout Tweets written in the United States?
|
|
Addictive Behaviors,
2022 |
|
|
[2]
|
When Silver Is As Good As Gold: Using Weak Supervision to Train Machine Learning Models on Social Media Data
|
|
2022 |
|
|
[3]
|
Instagram Posts Related to Alcohol Use on College Football Game Days after Implementation of an Alcohol Sales Policy
|
|
American Journal of Health …,
2022 |
|
|
[4]
|
Analyzing sentiments and themes on cannabis in Canada using 2018 to 2020 Twitter data
|
|
Journal of Cannabis …,
2022 |
|
|
[5]
|
Language-agnostic deep learning framework for automatic monitoring of population-level mental health from social networks
|
|
Journal of Biomedical …,
2022 |
|
|
[6]
|
Finding influential users in microblogs: state-of-the-art methods and open research challenges
|
|
2021 |
|
|
[7]
|
“I Still Don't Know What Happened, Complete Blackout”: a Content Analysis of Tweets Referencing Alcohol-Induced Amnesia
|
|
2021 |
|
|
[8]
|
MODELING ADDICTION AND DISEASE EPIDEMIOLOGY USING SOCIAL MEDIA
|
|
2020 |
|
|
[9]
|
Análisis de las redes sociales en el consumo de alcohol
|
|
2020 |
|
|
[10]
|
Drink2Vec: Improving the classification of alcohol-related tweets using distributional semantics and external contextual enrichment
|
|
2020 |
|
|
[11]
|
A scoping review of the use of Twitter for public health research
|
|
2020 |
|
|
[12]
|
Mining social media data for biomedical signals and health-related behavior
|
|
2020 |
|
|
[13]
|
Geographic Differences in Cannabis Conversations on Twitter: Infodemiology Study
|
|
2020 |
|
|
[14]
|
Online Searching and Social Media to Detect Alcohol Use Risk at Population Scale
|
|
2020 |
|
|
[15]
|
Methods to Improve Existing Heat Wave Surveillance Systems
|
|
2019 |
|
|
[16]
|
“Can't Wait to Blackout Tonight”: An Analysis of the Motives to Drink to Blackout Expressed on Twitter
|
|
2019 |
|
|
[17]
|
A New Frontier of the College Alcohol Culture:# SocialMedia
|
|
2019 |
|
|
[18]
|
drunktwitter: Examining the relations between
|
|
2018 |
|
|
[19]
|
Effective Method for Detecting Drunk Texting.
|
|
2018 |
|
|
[20]
|
Search worldwide, life-sciences literature
|
|
Drug and Alcohol Dependence,
2018 |
|
|
[21]
|
The number and characteristics of newspaper and Twitter reports on suicides and road traffic deaths in young people
|
|
2018 |
|
|
[22]
|
Improving the Classification of Drunk Texting in Tweets Using Semantic Enrichment
|
|
2018 |
|
|
[23]
|
Anticipatory Motivation for Drinking Alcohol: An In-Vivo Study
|
|
2018 |
|
|
[24]
|
The Case for Computational Health Science
|
|
Journal of Healthcare Informatics Research,
2018 |
|
|
[25]
|
Understanding Psycholinguistic Behavior of predominant drunk texters in Social Media
|
|
2018 |
|
|
[26]
|
140 Characters of Intoxication: Exploring the Prevalence of Alcohol-Related Tweets and Predicting Their Virality
|
|
SAGE Open,
2018 |
|
|
[27]
|
Toward Large-scale and Multi-facet Analysis of First Person Alcohol Drinking
|
|
2018 |
|
|
[28]
|
A Twitter-based study on the reach of a smoking cessation organisation and the social meaning of smoking
|
|
2018 |
|
|
[29]
|
# drunktwitter: Examining the relations between alcohol-related Twitter content and alcohol willingness and use among underage young adults
|
|
Drug and Alcohol Dependence,
2018 |
|
|
[30]
|
Supported Internet-Delivered Cognitive Behavior Treatment for Adults with Severe Depressive Symptoms: A Secondary Analysis
|
|
2018 |
|
|
[31]
|
From social media to public health surveillance: Word embedding based clustering method for twitter classification
|
|
2017 |
|
|
[32]
|
Monitoring obesity prevalence in the United States through bookmarking activities in online food portals
|
|
PLOS ONE,
2017 |
|
|
[33]
|
ソーシャルメディアを用いた依存症者の発言分類とその空間分析
|
|
2017 |
|
|
[34]
|
An investigation into digital alcohol marketing and user-created alcohol promotion, and the association with young adult's alcohol-related knowledge, attitudes, and …
|
|
2017 |
|
|
[35]
|
Social media responses to heat waves
|
|
International Journal of Biometeorology,
2017 |
|
|
[36]
|
Detecting Cognitive Distortions Through Machine Learning Text Analytics
|
|
2017 |
|
|
[37]
|
A Descriptive Study of the Prevalence and Typology of Alcohol-Related Posts in an Online Social Network for Smoking Cessation
|
|
2017 |
|
|
[38]
|
PREPRINT: Social Monitoring for Public Health
|
|
Synthesis Lectures on Information Concepts, Retrieval, and Services,
2017 |
|
|
[39]
|
Social Monitoring for Public Health
|
|
2017 |
|
|
[40]
|
Scaling Up Research on Drug Abuse and Addiction Through Social Media Big Data
|
|
Journal of medical Internet research,
2017 |
|
|
[41]
|
Social Media Correlates of Self-Reported Depressive Symptoms, Worry, and Social Anxiety
|
|
2017 |
|
|
[42]
|
Using social media to monitor mental health discussions− evidence from Twitter
|
|
2016 |
|
|
[43]
|
“When 'Bad'is 'Good'”: Identifying Personal Communication and Sentiment in Drug-Related Tweets
|
|
JMIR public health and surveillance,
2016 |
|
|
[44]
|
SOCIAL MEDIA MINING FOR PUBLIC HEALTH MONITORING AND SURVEILLANCE
|
|
2016 |
|
|
[45]
|
# ec: Findings and implications from a quantitative content analysis of tweets about emergency contraception
|
|
Digital Health,
2016 |
|
|
[46]
|
Social media and alcohol: Summary of research, intervention ideas and future study directions
|
|
2016 |
|
|
[47]
|
Young Adults' Exposure to Alcohol-and Marijuana-Related Content on Twitter
|
|
2016 |
|
|
[48]
|
“Those edibles hit hard”: Exploration of Twitter data on cannabis edibles in the US
|
|
Drug and Alcohol Dependence,
2016 |
|
|
[49]
|
Validating Machine Learning Algorithms for Twitter Data Against Established Measures of Suicidality
|
|
2016 |
|
|
[50]
|
A Smoking Cessation Campaign on Twitter: Understanding the Use of Twitter and Identifying Major Players in a Health Campaign
|
|
Journal of Environmental Science and Health, Part A: Toxic/Hazardous Substances and Environmental Engineering,
2016 |
|
|
[51]
|
Ethical issues in using Twitter for population-level depression monitoring: a qualitative study
|
|
2016 |
|
|
[52]
|
Marketing to Youth in the Digital Age: The Promotion of Unhealthy Products and Health Promoting Behaviours on Social Media
|
|
2016 |
|
|
[53]
|
THE JEKYLL AND HYDE OF OUR DRINKING: EVENT SPECIFIC DRINKING, INTERVENTION, AND PREVENTION
|
|
2016 |
|
|
[54]
|
Assessing situations on social media: Temporal, demographic, and personality influences on situation experience
|
|
ProQuest Dissertations Publishing,
2016 |
|
|
[55]
|
Maternal occupation during pregnancy, birth weight, and length of gestation: combined analysis of 13 European birth cohorts
|
|
2015 |
|
|
[56]
|
Introduction to the workshop on computational health science.
|
|
2015 |
|
|
[57]
|
Using Twitter to Survey Alcohol Use in the San Francisco Bay Area
|
|
Epidemiology,
2015 |
|
|
[58]
|
Analysing Twitter as an Opportunity to Understand Substance Use
|
|
Available at SSRN 2566850,
2015 |
|
|
[59]
|
Tracking suicide risk factors through Twitter in the US
|
|
Crisis,
2015 |
|
|
[60]
|
Influence of Social Media on Alcohol Use in Adolescents and Young Adults
|
|
Alcohol Research: Current Reviews,
2015 |
|
|
[61]
|
“Hey Everyone, I'm Drunk.” An Evaluation of Drinking-Related Twitter Chatter
|
|
Journal of studies on alcohol and drugs,
2015 |
|
|
[62]
|
Introduction to the workshop on computational health science
|
|
Proceedings of the 6th ACM Conference on Bioinformatics, Computational Biology and Health Informatics,
2015 |
|
|
[63]
|
Circadian Rhythms in Socializing Propensity
|
|
PloS one,
2015 |
|
|
[64]
|
“Time for dabs”: Analyzing Twitter data on marijuana concentrates across the US
|
|
Drug and alcohol dependence,
2015 |
|
|
[65]
|
Research opportunities at the intersection of social media and survey data
|
|
Current Opinion in Psychology,
2015 |
|
|
[66]
|
Use of Twitter to monitor attitudes toward depression and schizophrenia: an exploratory study
|
|
PeerJ,
2014 |
|
|
[67]
|
Online Course Management System for WIC Nutrition Education and Study of Its Effectiveness in Behavioral and Attitude Changes
|
|
NULL
2014 |
|
|
[68]
|
Ethical Issues in Using Twitter for Public Health Surveillance and Research: Developing a Taxonomy of Ethical Concepts From the Research Literature
|
|
Journal of medical Internet research,
2014 |
|
|
[69]
|
Impact of Social Media in Healthcare and Classification and Prediction of Swine Flu Related Tweets Using LDA Model
|
|
2014 |
|
|
[70]
|
Tracking suicide risk factors through Twitter in the US.
|
|
Crisis: The Journal of …,
2014 |
|
|
[71]
|
Computational Techniques for Public Health Surveillance
|
|
2013 |
|
|
[72]
|
Twitter and Public Health
|
|
Journal of Public Health Management and Practice,
2013 |
|
|
[73]
|
Using Twitter to examine smoking behavior and perceptions of emerging tobacco products
|
|
Journal of medical Internet research,
2013 |
|
|
[74]
|
Using Twitter for breast cancer prevention: an analysis of breast cancer awareness month
|
|
BMC cancer,
2013 |
|
|
[75]
|
" Right time, right place" health communication on Twitter: value and accuracy of location information
|
|
Journal of medical Internet research,
2012 |
|
|
[76]
|
Adolescent Health and Media
|
|
|
|
|