ReviewFrontiers in big data2019
Social Data: Biases, Methodological Pitfalls, and Ethical Boundaries.
Review in Frontiers in big data, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 80 papers, 3 of them syntheses 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
80 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Yoga and Tai chi: a cross-cultural comparative study of health benefits, cultural sustainability, and global public health implications.Frontiers in public health · 2026Pooled it
- A worldwide itinerary of research ethics in science for a better social responsibility and justice: a bibliometric analysis and review.Frontiers in research metrics and analytics · 2025Pooled it
- Machine Learning and Prediction in Fetal, Infant, and Toddler Neuroimaging: A Review and Primer.Biological psychiatry · 2023Pooled it
- LLM-based annotation and token-augmented modeling for emotional tone classification in online cancer peer-support posts.PLOS digital health · 2026Article
- Rapid Epidemiological Data Collection on Social Media for COVID-19: Comparative Study Between Online Surveys and Conventional Cohorts.Journal of medical Internet research · 2026Observational
- Comparison of Artificial Intelligence Tools With Human Coding for Sentiment, Topic, and Thematic Analysis Tasks of Public Health Datasets During the COVID-19 Pandemic in Australia: Case Study.Online journal of public health informatics · 2026Article
- Youth perceptions of urban waterfront environments for stress relief: a social media text analysis study in Beijing.Frontiers in public health · 2026Article
- Pragmatic lessons for harnessing social media for health research through digital data donation post-API access.npj digital public health · 2026Review
- Public sentiment and thematic evolution in the metaverse: A large-scale computational analysis of Twitter discourse.PloS one · 2026Article
- Discursive constructions of autism on social media: a multilingual analysis across five languages.Frontiers in psychology · 2026Article
- Ordinal sentiment classification in cancer support forums: a controlled benchmark of machine learning and transformer models.Frontiers in digital health · 2026Article
- Revisiting big data optimism: risks of data-driven black box algorithms for society.Ethics and information technology · 2026Article
- Exploring biases related to the use of large language models in a multilingual depression corpus.Scientific reports · 2025Article
- FanFAIR: sensitive data sets semi-automatic fairness assessment.BMC medical informatics and decision making · 2025Article
- Developing a Concept on Ethical, Legal and Social Implications (ELSI) for Data Literacy in Health Professions: A Learning Objective-Based Approach.Healthcare (Basel, Switzerland) · 2025Article
- Leveraging machine learning techniques for image classification and revealing social media insights into human engagement with urban wild spaces.Scientific reports · 2025Article
- Bias in artificial intelligence for medical imaging: fundamentals, detection, avoidance, mitigation, challenges, ethics, and prospects.Diagnostic and interventional radiology (Ankara, Turkey) · 2025Review
- Sex-Based Bias in Artificial Intelligence-Based Segmentation Models in Clinical Oncology.Clinical oncology (Royal College of Radiologists (Great Britain)) · 2025Review
- Large-scale analysis of fact-checked stories on Twitter reveals graded effects of ambiguity and falsehood on information reappearance.PNAS nexus · 2025Article
- Violence against women and girls research: Leveraging gains across disciplines.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
20 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Social data in digital form-including user-generated content, expressed or implicit relations between people, and behavioral traces-are at the core of popular applications and platforms, driving the research agenda of many researchers. The promises of social data are many, including understanding "what the world thinks" about a social issue, brand, celebrity, or other entity, as well as enabling better decision-making in a variety of fields including public policy, healthcare, and economics. Many academics and practitioners have warned against the naïve usage of social data. There are biases and inaccuracies occurring at the source of the data, but also introduced during processing. There are methodological limitations and pitfalls, as well as ethical boundaries and unexpected consequences that are often overlooked. This paper recognizes the rigor with which these issues are addressed by different researchers varies across a wide range. We identify a variety of menaces in the practices around social data use, and organize them in a framework that helps to identify them. "
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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.