ArticleInternational journal of environmental research and public health2018
Understanding #WorldEnvironmentDay User Opinions in Twitter: A Topic-Based Sentiment Analysis Approach.
Article in International journal of environmental research and public health, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 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
17 citing papers in PubMed, 173 citations in OpenAlex.
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- Understanding public discourse surrounding the impact of bitcoin on the environment in social media.GeoJournal · 2023Article
- Understanding Alcohol Use Discourse and Stigma Patterns in Perinatal Care on Twitter.Healthcare (Basel, Switzerland) · 2022Article
- Ecosystem Services: A Social and Semantic Network Analysis of Public Opinion on Twitter.International journal of environmental research and public health · 2022Article
- Integrating Natural Language Processing and Interpretive Thematic Analyses to Gain Human-Centered Design Insights on HIV Mobile Health: Proof-of-Concept Analysis.JMIR human factors · 2022Article
- Sentiment analysis of vegan related tweets using mutual information for feature selection.PeerJ. Computer science · 2022Article
- How Does Risk-Information Communication Affect the Rebound of Online Public Opinion of Public Emergencies in China?International journal of environmental research and public health · 2021Article
- How Social Media Comments Inform the Promotion of Mask-Wearing and Other COVID-19 Prevention Strategies.International journal of environmental research and public health · 2021Article
- Detection of Fake News Text Classification on COVID-19 Using Deep Learning Approaches.Computational and mathematical methods in medicine · 2021Article
- Making sense of tweets using sentiment analysis on closely related topics.Social network analysis and mining · 2021Article
- Gaining a deeper understanding of nutrition using social networks and user-generated content.Internet interventions · 2020Article
- Marketing challenges in the #MeToo era: gaining business insights using an exploratory sentiment analysis.Heliyon · 2020Article
- Mapping multispectral Digital Images using a Cloud Computing software: applications from UAV images.Heliyon · 2019Article
- The importance of behavioral data to identify online fake reviews for tourism businesses: a systematic review.PeerJ. Computer science · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The main objective of this exploratory study is to identify the social, economic, environmental and cultural factors related to the sustainable care of both environment and public health that most concern Twitter users. With 336 million active users as of 2018, Twitter is a social network that is increasingly used in research to get information and to understand public opinion as exemplified by Twitter users. In order to identify the factors related to the sustainable care of environment and public health, we have downloaded
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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.