Unmasking Human Trafficking Risk in Commercial Sex Supply Chains with Machine Learning

Published Online:https://doi.org/10.1287/msom.2022.0304

References

  • Albright E, D’Adamo K (2017) Decreasing human trafficking through sex work decriminalization. AMA J. Ethics 19(1):122–126.CrossrefGoogle Scholar
  • Anahideh H, Asudeh A, Thirumuruganathan S (2022) Fair active learning. Expert Systems Appl. 199:116981.CrossrefGoogle Scholar
  • Androff DK (2011) The problem of contemporary slavery: An international human rights challenge for social work. Internat. Soc. Work 54(2):209–222.CrossrefGoogle Scholar
  • Ash JT, Zhang C, Krishnamurthy A, Langford J, Agarwal A (2019) Deep batch active learning by diverse, uncertain gradient lower bounds. Preprint, submitted June 9, https://arxiv.org/abs/1906.03671.Google Scholar
  • Baird K, Connolly J (2023) Recruitment and entrapment pathways of minors into sex trafficking in Canada and the United States: A systematic review. Trauma Violence Abuse 24(1):189–202.CrossrefGoogle Scholar
  • Bilgic M, Mihalkova L, Getoor L (2010) Active learning for networked data. ICML’10 Proc. 27th Internat. Conf. Machine Learning (ICML-10) (Omnipress, Madison, WI), 79–86.Google Scholar
  • Chan H, Tran-Thanh L, Wilder B, Rice E, Vayanos P, Tambe M (2018) Utilizing housing resources for homeless youth through the lens of multiple multi-dimensional knapsacks. AIES’18 Proc. 2018 AAAI/ACM Conf. AI Ethics Soc. (Association for Computing Machinery, New York), 41–47.Google Scholar
  • Chen XW, Lin X (2014) Big data deep learning: Challenges and perspectives. IEEE Access 2:514–525.CrossrefGoogle Scholar
  • Citovsky G, DeSalvo G, Gentile C, Karydas L, Rajagopalan A, Rostamizadeh A, Kumar S (2021) Batch active learning at scale. NIPS’21 Proc. 35th Internat. Conf. Neural Inform. Processing Systems (Curran Associates Inc., Red Hook, NY), 11933–11944.Google Scholar
  • Dank ML, Khan B, Downey PM, Kotonias C, Mayer D, Owens C, Pacifici L, Yu L (2014) Estimating the size and structure of the underground commercial sex economy in eight major U.S. cities. Report, The Urban Institute, Washington, DC.Google Scholar
  • Dligach D, Palmer M (2011) Good seed makes a good crop: Accelerating active learning using language modeling. HLT’11 Proc. 49th Annual Meeting Assoc. Comput. Linguistics Human Language Tech. (Association for Computational Linguistics, Kerrville, TX), 6–10.Google Scholar
  • Dubrawski A, Miller K, Barnes M, Boecking B, Kennedy E (2015) Leveraging publicly available data to discern patterns of human-trafficking activity. J. Human Trafficking 1(1):65–85.CrossrefGoogle Scholar
  • FBI (2019) Operation independence day. FBI (August 6), https://www.fbi.gov/news/stories/operation-independence-day-2019.Google Scholar
  • FBI (2021) Human trafficking. Accessed March 2021, https://www.fbi.gov/investigate/violent-crime/human-trafficking.Google Scholar
  • Flynn C, Alston M, Mason R (2014) Trafficking in women for sexual exploitation: Building Australian knowledge. Internat. Soc. Work 57(1):27–38.CrossrefGoogle Scholar
  • Gensim (2021) Gensim 4.0.1. Accessed March 2021, https://www.snorkel.org/.Google Scholar
  • Gezinski LB, Gonzalez-Pons KM (2022) Sex trafficking and technology: A systematic review of recruitment and exploitation. J. Human Trafficking 10(3):497–511.CrossrefGoogle Scholar
  • Gonsior J, Thiele M, Lehner W (2020) WEAKAL: Combining active learning and weak supervision. Appice A, Tsoumakas G, Manolopoulos Y, Matwin S, eds. Internat. Conf. Discovery Sci., DS 2020, Lecture Notes in Computer Science, vol. 12323 (Springer, Cham, Switzerland), 34–49.Google Scholar
  • Government Accountability Office (2006) Human trafficking: Better data, strategy, and reporting needed to enhance us antitrafficking efforts abroad. Trends Organized Crime 10:16–38.CrossrefGoogle Scholar
  • Hall E, Dickson C, Schroh D, Wright W (2015) TellFinder: Discovering related content in big data (VIS). Report, Uncharted Software, Toronto.Google Scholar
  • Hardt M, Price E, Srebro N (2016) Equality of opportunity in supervised learning. NIPS’16 Proc. 30th Internat. Conf. Neural Inform. Processing Systems (Curran Associates Inc., Red Hook, NY), 3323–3331.Google Scholar
  • Heilemann T, Santhiveeran J (2011) How do female adolescents cope and survive the hardships of prostitution? A content analysis of existing literature. J. Ethnic Cultural Diversity Soc. Work 20(1):57–76.CrossrefGoogle Scholar
  • Hodge DR, Lietz CA (2007) The international sexual trafficking of women and children: A review of the literature. Affilia 22(2):163–174.CrossrefGoogle Scholar
  • ILO (2017) Human Trafficking by the Numbers (International Labor Organization, Geneva).Google Scholar
  • Johnson BC (2012) Aftercare for survivors of human trafficking. Soc. Work Christianity 39(4):370–389.Google Scholar
  • Jones L, Engstrom DW, Hilliard T, Diaz M (2007) Globalization and human trafficking. J. Soc. Soc. Welfare 34:107.Google Scholar
  • Jorgensen S, Sandoval P (2019) Experts: Trump’s tape bound women trafficking claim is misleading. CNN (January 28), https://www.cnn.com/2019/01/27/us/human-trafficking-fact-check/index.html.Google Scholar
  • Kangaspunta K, Sarrica F, Serio G, Kelly W, Samson J, Wills C (2020) Global report on trafficking in persons 2020. Report, United Nations Office on Drugs and Crime, Vienna.Google Scholar
  • Kaya YB, Maass KL, Dimas GL, Konrad R, Trapp AC, Dank M (2024) Improving access to housing and supportive services for runaway and homeless youth: Reducing vulnerability to human trafficking in New York City. IISE Trans. 56(3):296–310.Google Scholar
  • Kejriwal M, Kapoor R (2019) Network-theoretic information extraction quality assessment in the human trafficking domain. Appl. Network Sci. 4(1):1–26.CrossrefGoogle Scholar
  • Keskin BB, Bott GJ, Freeman NK (2021) Cracking sex trafficking: Data analysis, pattern recognition, and path prediction. Production Oper. Management 30(4):1110–1135.CrossrefGoogle Scholar
  • Kessler G (2018) Has the sex-trafficking law eliminated 90 percent of the sex trade. Washington Post (August 20), https://www.washingtonpost.com/politics/2018/08/20/has-sex-trafficking-law-eliminated-percent-sex-trafficking-ads/.Google Scholar
  • Konrad R, Maass KL, Trapp AC (2020) Perspectives on how to conduct responsible anti-human trafficking research in operations and analytics. Preprint, submitted June 30, https://arxiv.org/abs/2006.16445.Google Scholar
  • Konrad RA, Trapp AC, Palmbach TM, Blom JS (2017) Overcoming human trafficking via operations research and analytics: Opportunities for methods, models, and applications. Eur. J. Oper. Res. 259(2):733–745.CrossrefGoogle Scholar
  • Kosmas D, Melander C, Singerhouse E, Sharkey TC, Maass KL, Barrick K, Martin L (2022) A transdisciplinary approach for generating synthetic but realistic domestic sex trafficking networks. Preprint, submitted March 3, https://arxiv.org/abs/2203.01893.Google Scholar
  • Kotrla K (2010) Domestic minor sex trafficking in the United States. Soc. Work 55(2):181–187.CrossrefGoogle Scholar
  • Laczko F (2002) Human trafficking: The need for better data. Migration Inform. Source 1:61–80.Google Scholar
  • Latonero M (2011) Human trafficking online: The role of social networking sites and online classifieds. Preprint, submitted April 24, http://dx.doi.org/10.2139/ssrn.2045851.Google Scholar
  • Li R, Tobey M, Mayorga M, Caltagirone S, Özaltin O (2023) Detecting human trafficking: Automated classification of online customer reviews of massage businesses. Manufacturing Service Oper. Management 25(3):1051–1065.Google Scholar
  • Li L, Simek O, Lai A, Daggett M, Dagli CK, Jones C (2018) Detection and characterization of human trafficking networks using unsupervised scalable text template matching. 2018 IEEE Internat. Conf. Big Data (Big Data) (IEEE, Piscataway, NJ), 3111–3120.Google Scholar
  • Lopez-Martinez M (2020) Sex trafficking still a prevalent issue across Canada, advocates and police say. CTVNews (February 20), https://www.cnn.com/2019/01/27/us/human-trafficking-fact-check/index.html.Google Scholar
  • Maass KL, Trapp AC, Konrad R (2020) Optimizing placement of residential shelters for human trafficking survivors. Socio-Econom. Planning Sci. 70:100730.CrossrefGoogle Scholar
  • Martin L, Pierce A, Peyton S, Gabilondo AI, Tulpule G (2014) Mapping the market for sex with trafficked minor girls in Minneapolis: Structures, functions, and patterns. Robert J. Jones Urban Research and Outreach-Engagement Center Report, University of Minnesota Twin Cities, Minneapolis.Google Scholar
  • McCallumzy AK, Nigamy K (1998) Employing EM and pool-based active learning for text classification. ICML’98 Proc. Internat. Conf. Machine Learning (ICML) (Morgan Kaufmann Publishers Inc., San Francisco), 359–367.Google Scholar
  • McInnes L, Healy J, Melville J (2018) UMAP: Uniform manifold approximation and projection for dimension reduction. Preprint, submitted February 9, https://arxiv.org/abs/1802.03426.Google Scholar
  • Mikolov T, Chen K, Corrado G, Dean J (2013) Efficient estimation of word representations in vector space. Preprint, submitted January 16, https://arxiv.org/abs/1301.3781.Google Scholar
  • Murphy LT (2016) Labor and sex trafficking among homeless youth: A ten city study (executive summary). Modern Slavery Research Project, Loyola University, New Orleans, https://oag.ca.gov/sites/all/files/agweb/pdfs/ht/murphy-labor-sex-trafficking-homeless-youth.pdf.Google Scholar
  • Nashaat M, Miller J (2021) Improving news popularity estimation via weak supervision and meta-active learning. Proc. 54th Hawaii Internat. Conf. System Sci. (Association for Information Systems, Atlanta), 2679–2688.Google Scholar
  • Okech D, Choi YJ, Elkins J, Burns AC (2018) Seventeen years of human trafficking research in social work: A review of the literature. J. Evidence-Inform. Soc. Work 15(2):103–122.CrossrefGoogle Scholar
  • Olsson F (2009) A literature survey of active machine learning in the context of natural language processing. SICS Technical Report T2009:06, Swedish Institute of Computer Science, Kista, Sweden.Google Scholar
  • Orme J, Ross-Sheriff F (2015) Sex trafficking: Policies, programs, and services. Soc. Work 60(4):287–294.CrossrefGoogle Scholar
  • Pennington J, Socher R, Manning CD (2014) Glove: Global vectors for word representation. Proc. 2014 Conf. Empirical Methods Natural Language Processing (EMNLP) (Association for Computational Linguistics, Kerrville, TX), 1532–1543.Google Scholar
  • Potocky M (2010) The travesty of human trafficking: A decade of failed US policy. Soc. Work 55(4):373–375.CrossrefGoogle Scholar
  • Rabbany R, Bayani D, Dubrawski A (2018) Active search of connections for case building and combating human trafficking. PKDD’18 Proc. 24th ACM SIGKDD Internat. Conf. Knowledge Discovery Data Mining (Association for Computing Machinery, New York), 2120–2129.Google Scholar
  • Raets S, Janssens J (2019) Trafficking and technology: Exploring the role of digital communication technologies in the Belgian human trafficking business. Eur. J. Criminal Policy Res. 27:215–238.CrossrefGoogle Scholar
  • Rafferty Y (2008) The impact of trafficking on children: Psychological and social policy perspectives. Child Development Perspect. 2(1):13–18.CrossrefGoogle Scholar
  • Ratner A, Bach SH, Ehrenberg H, Fries J, Wu S, Ré C (2017) Snorkel: Rapid training data creation with weak supervision. Proc. VLDB Endowment 11(3):269–282.CrossrefGoogle Scholar
  • Rehurek R, Sojka P (2010) Software framework for topic modelling with large corpora. Proc. LREC 2010 Workshop New Challenges NLP Frameworks (University of Malta, Msida), 45–50.Google Scholar
  • Roby JL (2005) Women and children in the global sex trade: Toward more effective policy. Internat. Soc. Work 48(2):136–147.CrossrefGoogle Scholar
  • Roby JL, Vincent M (2017) Federal and state responses to domestic minor sex trafficking: The evolution of policy. Soc. Work 62(3):201–210.CrossrefGoogle Scholar
  • Rong X (2014) word2vec parameter learning explained. Preprint, submitted November 11, https://arxiv.org/abs/1411.2738.Google Scholar
  • Settles B (2009) Active learning literature survey. Computer Sciences Technical Report 1648, University of Wisconsin–Madison, Madison, WI.Google Scholar
  • Settles B (2012) Active Learning (Synthesis Lectures on Artificial Intelligence and Machine Learning) (Morgan and Claypool Publishers, San Rafael, CA).Google Scholar
  • Shively M, Kliorys K, Wheeler K, Hunt D (2012) A national overview of prostitution and sex trafficking demand reduction efforts. Final report, Abt Associates Inc., Cambridge, MA.Google Scholar
  • Snorkel (2021) Snorkel. Accessed May 2021, https://www.snorkel.org/.Google Scholar
  • Symeonidis S, Effrosynidis D, Arampatzis A (2018) A comparative evaluation of pre-processing techniques and their interactions for Twitter sentiment analysis. Expert Systems Appl. 110:298–310.CrossrefGoogle Scholar
  • TellFinder (2021) TellFinder Alliance: A global counter-human trafficking partner network, empowered by data. Accessed June 2021, https://www.tellfinderalliance.com/.Google Scholar
  • UNODC (2020) UNODC Human Trafficking Case Law Database (United Nations Office on Drugs and Crime, Vienna).Google Scholar
  • Witte M (2018) The anti-trafficking movement needs better data to solve the problem, Stanford researchers say. Stanford News Service (September 5), https://news.stanford.edu/stories/2018/09/get-good-data-human-trafficking.Google Scholar
  • Yang Y, Ma Z, Nie F, Chang X, Hauptmann AG (2015) Multi-class active learning by uncertainty sampling with diversity maximization. Internat. J. Comput. Vision 113(2):113–127.CrossrefGoogle Scholar
  • Zhang C, Ré C, Cafarella M, De Sa C, Ratner A, Shin J, Wang F, Wu S (2017) DeepDive: Declarative knowledge base construction. Comm. ACM 60(5):93–102.CrossrefGoogle Scholar
  • Zhou ZH (2018) A brief introduction to weakly supervised learning. National Sci. Rev. 5(1):44–53.CrossrefGoogle Scholar
  • Zhu J, Li L, Jones C (2019) Identification and detection of human trafficking using language models. 2019 Eur. Intelligence Security Informatics Conf. (EISIC) (IEEE, Piscataway, NJ), 24–31.Google Scholar
  • Zhu J, Wang H, Hovy E, Ma M (2010) Confidence-based stopping criteria for active learning for data annotation. ACM Trans. Speech Language Processing 6(3):1–24.CrossrefGoogle Scholar
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