ArticleJournal of big data2022
Modeling the public attitude towards organic foods: a big data and text mining approach.
Article in Journal of big data, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
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
9 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Emerging Technologies for Investigating Food Consumer Behavior: A Systematic Review.Comprehensive reviews in food science and food safety · 2025Pooled it
- Content hubs, information flows, and reactions for pesticide-related discussions on Twitter/X.Integrated environmental assessment and management · 2025Article
- Article
- Application of artistic design innovation in promoting rural cultural brand construction.Scientific reports · 2024Article
- Do Consumers Value Agri-Food Industries' Environmental Commitment? The Case of the Table Olive Industry.Foods (Basel, Switzerland) · 2024Article
- A Comprehensive Analysis of Organic Food: Evaluating Nutritional Value and Impact on Human Health.Foods (Basel, Switzerland) · 2024Review
- Exploring public opinion on health effects of prepared dishes in China through social media comments.Frontiers in public health · 2024Article
- Green-Labelled Rice versus Conventional Rice: Perception and Emotion of Chinese Consumers Based on Review Mining.Foods (Basel, Switzerland) · 2022Article
- Social Media and Chronic Pain: What Do Patients Discuss?Journal of personalized medicine · 2022Article
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
No grant is acknowledged in the PubMed record.
Abstract
This study aims to identify the topics that users post on Twitter about organic foods and to analyze the emotion-based sentiment of those tweets. The study addresses a call for an application of big data and text mining in different fields of research, as well as proposes more objective research methods in studies on food consumption. There is a growing interest in understanding consumer choices for foods which are caused by the predominant contribution of the food industry to climate change. So far, customer attitudes towards organic food have been studied mostly with self-reported methods, such as questionnaires and interviews, which have many limitations. Therefore, in the present study, we used big data and text mining techniques as more objective methods to analyze the public attitude about organic foods. A total of 43,724 Twitter posts were extracted with streaming Application Programming Interface (API). Latent Dirichlet Allocation (LDA) algorithm was applied for topic modeling. A test of topic significance was performed to evaluate the quality of the topics. Public sentiment was analyzed based on the NRC emotion lexicon by utilizing
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.