Research evidence · snapshot 22 July 2026
What academic research adds to dating-safety advice.
Platform safety pages tell people what to do. Research helps explain how pressure, consent, privacy, design, and support can work across different dating situations. This library keeps the population, evidence type, and limit beside every source.
The boundary
Research explains patterns. It does not identify a person.
None of these studies is turned into a private risk score, a criminal conclusion, or a claim about someone a reader is dating. The useful translation is a safer next question: what is being requested, how fast is the pressure moving, what can stay private, and what can wait?
Core evidence layer
Six research areas we use first.
These are the strongest fits for the report’s current questions: private images, consent, platform design, stage changes, support, and emerging manipulation. They are not six claims that every dating interaction follows the same path.
Digital dating violence, pressured sexting, and image-based abuse
Joris Van Ouytsel and collaborators
- Evidence type
- Peer-reviewed research listed through a university profile
- Population or scope
- Much of the cited work concerns adolescents and young people, including heterosexual and LGBTQ+ youth.
What it adds: It helps explain why a private-image request is a safety decision involving pressure, consent, privacy, and possible later harm, not merely a question of whether a profile looks real.
Used here for: Private-photo, sexting, image-sharing, and “prove you trust me” guidance.
Limit: These studies do not provide an all-age prevalence estimate or a person-level detector. A pressured request is a reason to pause, not proof of criminal intent.
Consent and AI-generated self-presentation in online dating
Douglas Zytko and collaborators
- Evidence type
- Emerging peer-reviewed qualitative survey research
- Population or scope
- 113 online daters who reported using AI-generated profile or message content.
What it adds: It puts disclosure and informed consent on the safety map: polished language or a fast emotional connection may be shaped by a tool, and that possibility cannot be settled by a verification badge.
Used here for: Verification limits, AI-assisted profiles and messages, and the difference between a presentation signal and a person’s underlying story.
Limit: The study does not show that AI use causes harm, that undisclosed AI use is always deceptive, or that a particular person used AI.
CHI 2026 paper: AI-generated self-presentation on dating apps
Dating-app design, safety policy, marginalized users, and surveillance
Christopher Dietzel, Stefanie Duguay, Diana Parry, and collaborators
- Evidence type
- Academic analysis of dating-app safety approaches
- Population or scope
- The work addresses dating-app users and the unequal effects of platform safety approaches, with attention to marginalized users.
What it adds: It prevents a common mistake: treating safety as only the user’s responsibility. A feature can help in one moment while also creating privacy, policing, or exclusion concerns for another user.
Used here for: Report and support guidance, privacy boundaries, and the section explaining why we do not rank platforms or promise that a feature prevents harm.
Limit: This is not an app ranking, an incident-rate comparison, or proof that every platform feature has the same effect in every community.
Mapping safety, risk, and support across dating-app use
Diana Parry and collaborators
- Evidence type
- University research project and public education tool
- Population or scope
- People navigating dating-app safety, risk, and support; the public launch describes a cross-context mapping approach.
What it adds: It offers a useful information architecture: safety is a route through several moments and support options, not a single badge or a final verdict.
Used here for: The report’s stage-based risk path, community context, and links to support or reporting routes.
Limit: The existence of a map or guide is not an outcome evaluation. It does not prove that a user will be safe or that one route fits every location.
Relationship development and movement between online and offline settings
Liesel Sharabi and collaborators
- Evidence type
- Relationship and communication research
- Population or scope
- Research on mate selection, relationship initiation, dating apps, and online-to-offline relationship development.
What it adds: It helps describe the transition from app chat to another channel or an in-person meeting as a change in context, not as an automatic sign of danger.
Used here for: The “common risk path” sequence and advice to reassess privacy, pressure, and reversibility at each stage.
Limit: This is not a romance-scam prevalence study and does not establish a universal safe timeline for moving off-app or meeting.
AI-enabled romance scams and support for older adults
Sanchari Das and Ruba Abu-Salma with collaborators
- Evidence type
- Research-in-progress / funded project announcement
- Population or scope
- The announced project focuses on older adults and reports a planned international research scope.
What it adds: It keeps emerging AI-enabled manipulation and family or community support in view without treating an older person’s age as a diagnosis of vulnerability.
Used here for: Emerging-threat context and advice about involving a trusted person when pressure, isolation, or money requests make decisions harder.
Limit: This announcement is not a completed peer-reviewed finding. It must not be used to claim that older adults are uniformly more likely to be deceived.
Additional context
A useful language study, kept narrow.
Language patterns and manipulation in romance fraud
Pamela B. Faber · University of Granada
It supports teaching about repeated language moves such as accelerated intimacy or pressure without pretending that a phrase can identify a scammer.
Our limit: Corpus provenance, consent, representativeness, and context matter. We do not publish the corpus, reproduce private messages, or infer intent from wording alone.
Read the university sourceHow we use research
Four rules keep the translation honest.
- Keep the population visible. A study of young people, LGBTQ+ users, older adults, or a particular country is not silently rewritten as a global adult finding.
- Keep the evidence type visible. A peer-reviewed paper, a university tool, a faculty publication list, and a funded research announcement do not carry the same weight.
- Translate mechanisms into choices. We turn research into questions about timing, pressure, disclosure, privacy, consent, and support, not a label for another person.
- Do not publish sensitive material. We do not reproduce private chats, publish a person-search corpus, investigate incidents, or infer criminality from language or behavior.
Use the evidence in context
Read the report’s findings and sources together.
The Dating Safety Signals Report combines academic evidence with official platform guidance and independent public sources. Those layers answer different questions and are kept separate.
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