- cyber slavery; mass victimisation; criminal dynamics; digital platforms; digital footprints; syndicate
- https://doi.org/10.63621/ ajcjfs/1.2026.04
- Pages 4-14
The purpose of the study was to investigate the use of social media by law enforcement agencies to detect and investigate organised crime in the Philippines. The study used a set of complementary methods: an analytical and applied approach based on secondary data analysis, a method of system structural analysis, an analytical and synthetic method, a case study, and a method of analysing social networks. It was proved that Open Source Intelligence and Social Network Analysis were transformed into the basis of the Intelligence-Led Policing strategy. It was determined that such methodological integration allows investigators to convert fragmented digital traces into verified physical coordinates of criminal hubs. This proved the feasibility of switching from traditional mass arrests to a strategy of spot neutralisation of key network nodes (brokers and organisers) identified using centrality metrics. This justified the strategic transition from reactive arrests to point-by-point neutralisation of key network nodes (brokers and organisers) identified through network analysis. In the context of the study, a number of practical recommendations were developed aimed at institutionalising the M-SNOS methodology in law enforcement agencies in the Philippines. The developed practical recommendations summarised the need to institutionalise hybrid counteraction by creating a Joint Digital Intelligence Fusion Centre and reorienting the operational strategy to point-by-point neutralisation of key network nodes. The practical significance of the results lies in the fact that law enforcement organisations and technology platforms (Meta, TikTok) can use them to institutionalise the M-SNOS model and implement the legal and operational protocols necessary for a systematic fight against transnational cybercrime
References
- Act of the Republic of the Philippines No. 10173. (2012, August). Retrieved from https://privacy.gov.ph/data-privacy-act/.
- Act of the Republic of the Philippines No. 10175. (2012, September). Retrieved from https://lawphil.net/statutes/repacts/ra2012/ra_10175_2012.html.
- Akhgar, B., Bayerl, P.S., & Sampson, F. (Eds.). (2016). Open source intelligence investigation: From strategy to implementation. Cham: Springer. doi: 10.1007/978-3-319-47671-1.
- Business & Human Rights Resource Centre. (2025). Philippines: Over 70,000 illegal job posts targeting prospective migrant workers taken down from Facebook & TikTok; incl. co. responses. Retrieved from https://www.business-humanrights.org/ru/%D1%81%D0%B2%D0%B5%D0%B6%D0%B8%D0%B5-%D0%BD%D0%BE%D0%B2%D0%BE%D1%81%D1%82%D0%B8/philippines-over-70000-illegal-job-posts-targeting-prospective-migrant-workers-taken-down-from-facebook-tiktok-incl-cos-responses/.
- Caliwan, C.L. (2024). 99 workers nabbed in Parañaque scam hub raid. Retrieved from https://www.pna.gov.ph/articles/1231756.
- Dekens, N. (2025). The 13 biggest OSINT investigation challenges. ShadowDragon Blog. Retrieved from https://shadowdragon.io/blog/what-are-the-common-struggles-of-osint-investigations/.
- Donny, C.E.A.K., & Zulkifli, N. (2025). Organized crime: The comparative analysis of human trafficking and money laundering (case study: Malaysia-Philippines 2018-2022). International Journal of Social Sciences and Management Review, 8(3), 18-34. doi: 10.37602/ijssmr.2025.8303.
- Duan Xiong, W., & Yu Chong, W. (2024). Research on the application of social network data mining technology in crime analysis and prevention. Applied Mathematics and Nonlinear Sciences, 9(1), 1-12. doi: 10.2478/amns-2024-1832.
- Fernández-Planells, A., Orduña-Malea, E., & Feixa Pàmpols, C. (2021). Gangs and social media: A systematic literature review and an identification of future challenges, risks and recommendations. New Media & Society, 23(7), 2099-2124. doi: 10.1177/1461444821994490.
- Hababag, B.G., Alcantara, L.P., Tale, B., & Rogers, J.K. (2024). A social network analysis on Abu Sayyaf kidnappings. Southeastern Philippines Journal of Research and Development, 29(2), 211-228. doi: 10.53899/spjrd.v29i2.258.
- Howe, S. (2025). Social media statistics in the Philippines. Meltwater. Retrieved from https://www.meltwater.com/en/blog/social-media-statistics-philippines.
- Hsiao, Y., Leverso, J., & Papachristos, A.V. (2023). The corner, the crew, and the digital street: Multiplex networks of gang online-offline conflict dynamics in the digital age. American Sociological Review, 88(4), 709-741. doi: 10.1177/00031224231184268.
- Hutagalung, R., & Lubis, R.H. (2025). Triangular synergy model to enhance the Indonesian National Police’s (POLRI) strategy in handling human trafficking of cyber-based slavery. Journal of Information Systems Engineering and Management, 10(49s), 27-34. doi: 10.52783/jisem.v10i49s.9805.
- Lebert, D. (2025). Using social network analysis to combat organized crime. International Journal on Criminology, 12(1), 1-18. doi: 10.18278/ijc.12.1.1.
- Maldonado Ruiz, L.M. (2025). Criminogenic elements of information technologies and the proliferation of computer crime. Investigación Tecnología e Innovación, 17(23), 41-51. doi: 10.53591/iti.v17i23.1945.
- Moraes, M. de P. da S. (2016). Open source intelligence (OSINT) tools in virtual social networks as resources in cybercrime investigations. (Undergraduate thesis, Faculdades Integradas da Upis (UPIS), Brasília, Brazil). doi: 10.29327/44190052.
- Philippines rescues more than 1,000 trafficking victims used to run online scams. (2023). Retrieved from https://www.abc.net.au/news/2023-05-06/philippines-rescues-more-than-1-000-trafficking-victims/102312936.
- Philippines suspected digital fraud rate higher than global level for fifth consecutive year. (2025). Retrieved from https://newsroom.transunion.ph/philippines-suspected-digital-fraud-rate-higher-than-global-level-for-fifth-consecutive-year/.
- Philippines: Global Organised Crime Index. (2025). Retrieved from https://ocindex.net/country/philippines.
- Robertson, C., Bouchard, M., Whelan, C., & Girn, A. (2025). Untangling SNA: The use and underuse of social network analysis among crime analysts. CrimRxiv. doi: 10.21428/cb6ab371.e31eeea5.
- Rosenkranz, P., & Honekamp, W. (2022). Determination of movement profiles based on open-source data from social media. In Mobility in a globalised world 2021 (pp. 247-256). Bamberg: University of Bamberg Press. doi: 10.20378/irb-58356.
- Salonen, J., & Guarino, A. (2024). Art crime does not pay: Multiplexed social network analysis in cultural heritage trafficking forensics. In Proceedings of the 19th international conference on cyber warfare and security (pp. 617-620). Reading: Academic Conferences International. doi: 10.34190/iccws.19.1.2066.
- Soni, N., & Poonia, R. (2025). Enhancing digital forensics with AI-Driven OSINT: A proactive approach to cybercrime investigation. doi: 10.21203/rs.3.rs-6581767/v1.
- Suarmita, I.G.N.A., & Purnomo, H. (2024). Challenges of hybrid policing in countering online fraud networks: A case study from Sidrap Regency. Al-Ishlah: Jurnal Ilmiah Hukum, 27(1), 17-30. doi: 10.56087/aijih.v27i1.442.
- Supreme Court of the Republic Philippines No. 01-7-01-SC “Rules on Electronic Evidence”. (2001, July). Retrieved from https://www.doj.gov.ph/files/rules%20on%20electronic%20evidence.pdf.
- Suspected digital fraud rate in PH exceeds global average for fifth year in a row: Report. (2025). InsiderPH. Retrieved from https://insiderph.com/suspected-digital-fraud-rate-in-ph-exceeds-global-average-for-fifth-year-in-a-row-report.
- Telegram fueling crime in Southeast Asia as criminal networks flourish. (2024). YouTube. Retrieved from https://www.youtube.com/watch?v=PkEnYY_7RUk.
- Tkachova, O.V. (2022). Transnational crime: Features and basic models. Theory and Practice of Jurisprudence, 2(20), 240-251. doi: 10.21564/2225-6555.2021.2.245462.
- Troncoso, F., & Weber, R. (2024). The Steiner tree Prosecutor: Revealing and disrupting criminal networks through a single suspect. PLOS ONE, 19(12), article number e0312827. doi: 10.1371/journal.pone.0312827.
- United Nations Office on Drugs and Crime. (2024). Transnational organized crime and the convergence of cyber-enabled fraud, underground banking and technological innovation in Southeast Asia: A shifting threat landscape. Retrieved from https://www.unodc.org/roseap/uploads/documents/Publications/2024/TOC_Convergence_Report_2024.pdf.
- Woźnica, R. (2021). Organized crime and state capture in the Western Balkans. Rocznik Instytutu Europy Środkowo-Wschodniej, 19(4), 287-306. doi: 10.36874/RIESW.2021.4.14.
- Yuan, X., Mahabir, R., Crooks, A., & Croitoru, A. (2022). Achieving situational awareness of drug cartels with geolocated social media. GeoJournal, 87(5), 3453-3471. doi: 10.1007/s10708-021-10433-2.
- Zhao, K., Zhang, H., Li, J., Pan, Q., Lai, L., Nie, Y., & Zhang, Z. (2024). Social network forensics analysis model based on network representation learning. Entropy, 26(7), article number 579. doi: 10.3390/e26070579.