ArticlePloS one2019
Twitter-based measures of neighborhood sentiment as predictors of residential population health.
Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
16 citing papers in PubMed.
- Digital Epidemiology of Prescription Drug References on X (Formerly Twitter): Neural Network Topic Modeling and Sentiment Analysis.Journal of medical Internet research · 2024Article
- Effects of extreme temperatures on public sentiment in 49 Chinese cities.Scientific reports · 2024Article
- Uses of Social Determinants of Health Data to Address Cardiovascular Disease and Health Equity: A Scoping Review.Journal of the American Heart Association · 2023Article
- Predicting U.S. county opioid poisoning mortality from multi-modal social media and psychological self-report data.Scientific reports · 2023Article
- Filling in the white space: Spatial interpolation with Gaussian processes and social media data.Current research in ecological and social psychology · 2023Article
- Spatial and sentiment analysis of public opinion toward COVID-19 pandemic using twitter data: At the early stage of vaccination.International journal of disaster risk reduction : IJDRR · 2022Article
- Thinking Aloud or Screaming Inside: Exploratory Study of Sentiment Around Work.JMIR formative research · 2022Article
- Methods to Establish Race or Ethnicity of Twitter Users: Scoping Review.Journal of medical Internet research · 2022Article
- Article
- The Use of Social Media for Health Research Purposes: Scoping Review.Journal of medical Internet research · 2021Article
- Socioeconomic factors analysis for COVID-19 US reopening sentiment with Twitter and census data.Heliyon · 2021Article
- Examination of Community Sentiment Dynamics due to COVID-19 Pandemic: A Case Study from a State in Australia.SN computer science · 2021Article
- A graph-based approach for population health analysis using Geo-tagged tweets.Multimedia tools and applications · 2021Article
- Evaluating Asthma Mobile Apps to Improve Asthma Self-Management: User Ratings and Sentiment Analysis of Publicly Available Apps.JMIR mHealth and uHealth · 2020Article
- Social Media Responses to Elective Surgery Cancellations in the Wake of COVID-19.Annals of surgery · 2020Article
- Estimating geographic subjective well-being from Twitter: A comparison of dictionary and data-driven language methods.Proceedings of the National Academy of Sciences of the United States of America · 2020Article
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
Several studies have recently applied sentiment-based lexicons to Twitter to gauge local sentiment to understand health behaviors and outcomes for local areas. While this research has demonstrated the vast potential of this approach, lingering questions remain regarding the validity of Twitter mining and surveillance in local health research. First, how well does this approach predict health outcomes at very local scales, such as neighborhoods? Second, how robust are the findings garnered from sentiment signals when accounting for spatial effects? To evaluate these questions, we link 2,076,025 tweets from 66,219 distinct users in the city of San Diego over the period of 2014-12-06 to 2017-05-24 to the 500 Cities Project data and 2010-2014 American Community Survey data. We determine how well sentiment predicts self-rated mental health, sleep quality, and heart disease at a census tract level, controlling for neighborhood characteristics and spatial autocorrelation. We find that sentiment is related to some outcomes on its own, but these relationships are not present when controlling for other neighborhood factors. Evaluating our encoding strategy more closely, we discuss the limitations of existing measures of neighborhood sentiment, calling for more attention to how race/ethnicity and socio-economic status play into inferences drawn from such measures.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.