Mobile Money Phone Scam Survey Dataset
Abstract
The 2025 field survey contains 783 questionnaire responses from participants aged 18 or older, collected in Dang, Ngaoundéré, and surrounding areas. The initial dataset contained 800 responses; 17 records from respondents under 18 were excluded from both public language versions. The survey records mobile money use, scam awareness, victimization, scam methods, financial losses, reporting behavior, detection knowledge, and prevention needs. French and English versions are provided. The 2026 collection contains 30 retained online questionnaire responses and 25 anonymized interview transcripts from Ngaoundéré, provided in separate worksheets. They describe contact channels, identities claimed by scammers, scam approaches, and participants’ reactions. No summaries from external online sources are included. The archive includes the 2025 questionnaires in French and English and the 2026 questionnaire in French, the Python translation script and its lookup tables, audio transcription scripts and documentation, and the reviewed classification of the 25 interview transcripts. The original audio recordings are not publicly deposited because they contain personal information. Identifying details were removed from the published transcripts. Requests to consult the recordings for source verification may be considered subject to participant consent and confidentiality safeguards. The dataset is intended for academic research on cybersecurity, digital finance, fraud prevention, and user awareness. The 2026 records are analyzed separately from the 783 retained survey responses from 2025. All accounts describe self-reported experiences and do not independently establish that each reported incident occurred.
Fields of Study & Subjects
Cybercrime and Law Enforcement Studies
Spam and Phishing Detection
Information and Cyber Security
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 9 January 2026
- Language
- EN
- Document type
- Dataset