ArticleJournal of forensic and legal medicine2018
A survey of social media data analysis for physical activity surveillance.
Article in Journal of forensic and legal medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
13 citing papers in PubMed.
- Attitudes of Chinese public towards the autism community: Evidence from a decade of Weibo data.Heliyon · 2024Article
- Research on the death psychology among Chinese during and after the COVID-19 pandemic.Scientific reports · 2024Article
- Patterns in negative emotions, sleep disorders, and temperature: Evidence from microblog big data.Heliyon · 2023Article
- Analyzing sentiments and themes on cannabis in Canada using 2018 to 2020 Twitter data.Journal of cannabis research · 2022Article
- Geographical and Temporal Analysis of Tweets Related to COVID-19 and Cardiovascular Disease in the US.Annals of GIS · 2022Article
- The Feasibility of Using Instagram Data to Predict Exercise Identity and Physical Activity Levels: Cross-sectional Observational Study.Journal of medical Internet research · 2021Observational
- Over a decade of social opinion mining: a systematic review.Artificial intelligence review · 2021Article
- Geographic Differences in Cannabis Conversations on Twitter: Infodemiology Study.JMIR public health and surveillance · 2020Article
- Keeping up with the times: how national public health and governmental organizations communicate about cannabis on Twitter.Substance abuse treatment, prevention, and policy · 2019Article
- Monitoring Physical Activity Levels Using Twitter Data: Infodemiology Study.Journal of medical Internet research · 2019Article
- Characterizing Depression Issues on Sina Weibo.International journal of environmental research and public health · 2018Article
- Online Influence and Sentiment of Fitness Tweets: Analysis of Two Million Fitness Tweets.JMIR public health and surveillance · 2017Article
- The Relationship Between Social Media Data and Crime Rates in the United States.Social media + societyArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Social media data can provide valuable information regarding people's behaviors and health outcomes. Previous studies have shown that social media data can be extracted to monitor and predict infectious disease outbreaks. These same approaches can be applied to other fields including physical activity research and forensic science. Social media data have the potential to provide real-time monitoring and prediction of physical activity level in a given region. This tool can be valuable to public health organizations as it can overcome the time lag in the reporting of physical activity epidemiology data faced by traditional research methods (e.g. surveys, observational studies). As a result, this tool could help public health organizations better mobilize and target physical activity interventions. The first part of this paper aims to describe current approaches (e.g. topic modeling, sentiment analysis and social network analysis) that could be used to analyze social media data to provide real-time monitoring of physical activity level. The second aim of this paper was to discuss ways to apply social media analysis to other fields such as forensic sciences and provide recommendations to further social media research.
Indexed as
Identifiers
What OpenQuestion holds
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.