SynthesisPloS one2018
What demographic attributes do our digital footprints reveal? A systematic review.
Synthesis in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 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
20 citing papers in PubMed.
- A Social Identity Theory of Digital Identity.Perspectives on psychological science : a journal of the Association for Psychological Science · 2026Article
- BERTopic_Teen: a multi-module optimization approach for short text topic modeling in adolescent health.Frontiers in public health · 2025Article
- Overcoming biases of individual level shopping history data in health research.NPJ digital medicine · 2024Review
- Blinding to Circumvent Human Biases: Deliberate Ignorance in Humans, Institutions, and Machines.Perspectives on psychological science : a journal of the Association for Psychological Science · 2024Article
- Methods and Annotated Data Sets Used to Predict the Gender and Age of Twitter Users: Scoping Review.Journal of medical Internet research · 2024Article
- The persuasive effects of political microtargeting in the age of generative artificial intelligence.PNAS nexus · 2024Article
- Editorial: Theories, methods, practices, and fields of digital social research.Frontiers in sociology · 2024Article
- Navigating pathways to automated personality prediction: a comparative study of small and medium language models.Frontiers in big data · 2024Article
- Incorporating Psychological Science Into Policy Making: The Case of Misinformation.European psychologist · 2023Article
- Development and Assessment of a Social Media-Based Construct of Firearm Ownership: Computational Derivation and Benchmark Comparison.Journal of medical Internet research · 2023Article
- An Assessment of Perspectives and Concerns Among Research Participants of Childbearing Age Regarding the Health-Relatedness of Data, Online Data Privacy, and Donating Data to Researchers: Survey Study.Journal of medical Internet research · 2023Article
- Social world knowledge: Modeling and applications.PloS one · 2023Article
- A survey of United States adult privacy perspectives and willingness to share real-world data.Journal of clinical and translational science · 2023Article
- Generalizable Natural Language Processing Framework for Migraine Reporting from Social Media.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2023Article
- A Survey of Research Participants' Privacy-Related Experiences and Willingness to Share Real-World Data with Researchers.Journal of personalized medicine · 2022Article
- Methods to Establish Race or Ethnicity of Twitter Users: Scoping Review.Journal of medical Internet research · 2022Article
- Boosting people's ability to detect microtargeted advertising.Scientific reports · 2021Article
- Predicting Age Groups of Reddit Users Based on Posting Behavior and Metadata: Classification Model Development and Validation.JMIR public health and surveillance · 2021Article
- Location inference for hidden population with online text analysis.International journal of health geographics · 2020Article
- Citizens Versus the Internet: Confronting Digital Challenges With Cognitive Tools.Psychological science in the public interest : a journal of the American Psychological Society · 2020Review
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
To what extent does our online activity reveal who we are? Recent research has demonstrated that the digital traces left by individuals as they browse and interact with others online may reveal who they are and what their interests may be. In the present paper we report a systematic review that synthesises current evidence on predicting demographic attributes from online digital traces. Studies were included if they met the following criteria: (i) they reported findings where at least one demographic attribute was predicted/inferred from at least one form of digital footprint, (ii) the method of prediction was automated, and (iii) the traces were either visible (e.g. tweets) or non-visible (e.g. clickstreams). We identified 327 studies published up until October 2018. Across these articles, 14 demographic attributes were successfully inferred from digital traces; the most studied included gender, age, location, and political orientation. For each of the demographic attributes identified, we provide a database containing the platforms and digital traces examined, sample sizes, accuracy measures and the classification methods applied. Finally, we discuss the main research trends/findings, methodological approaches and recommend directions for future 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.