Abstract
Human trafficking that aims at the sexual exploitation of minors is a problem that affects the world; this crime has evolved with the use of the Internet. To make a contribution that facilitates the work of the Police, we have developed a method that uses Natural Language Processing and Image Processing techniques to detect messages on Twitter related to this felony. If minors are used for sexual exploitation, the Law in most countries, consider them human trafficking victims. The system has two phases to recognize the gender and age group of very young people. In the first one, it captures Twitter messages that are suspicious of being related to the crime through specific normalized hashtags. In the second phase, the system recognizes gender and age groups using facial features and or upper body geometry and proportions using Haar filters and SVM algorithm.
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References
Laczko, F.: Data and research on human trafficking. Int. Migr. 43(1–2), 5–16 (2005)
The statistics portal, Twitter: number of monthly active users 2010–2018. https://www.statista.com
Candes, M.R.: The Victims of Trafficking and Violence Protection Act of 2000: will it become the thirteenth amendment of the twenty-firsts century. U. Miami Inter-Am. L. Rev., 106–386 (2001)
Hughes, D.: Wilberforce can be free again: protecting trafficking victims. National Review Online (2008)
Hernández-Álvarez, M.: Detection of possible human trafficking in Twitter. In: International Conference on Information Systems and Software Technologies, pp. 187–191. IEEE (2019)
Alvari, H., Shakarian, P., Snyder, J.K.: A non-parametric learning approach to identify online human trafficking. IEEE Conference on Intelligence and Security Informatics, pp. 133–138. IEEE (2016)
Dehshibi, M.M., Bastanfard, A.: A new algorithm for age recognition from facial images. Sig. Process. 90(8), 2431–2444 (2010)
Alegria, I., Aranberri, N., Comas Umbert, P.R., Fresno, V., Gamallo, P., Padró, L., San Vicente Roncal, I., Turmo Borras, J., Zubiaga, A.: TweetNorm_ES: an annotated corpus for Spanish microtext normalization. In: Proceedings of the Ninth International Conference on Language Resources and Evaluation. European Language Resources Association, pp. 2274–2278 (2014)
Mena, A.P., Mayoral, M.B., Díaz-Lópe, E.: Comparative study of the features used by algorithms based on Viola and Jones face detection algorithm. In: International Work-Conference on the Interplay Between Natural and Artificial Computation, pp. 175–183. Springer, Cham (2015)
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Hernández-Álvarez, M., Granizo, S.L. (2021). Detection of Human Trafficking Ads in Twitter Using Natural Language Processing and Image Processing. In: Ahram, T. (eds) Advances in Artificial Intelligence, Software and Systems Engineering. AHFE 2020. Advances in Intelligent Systems and Computing, vol 1213. Springer, Cham. https://doi.org/10.1007/978-3-030-51328-3_12
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DOI: https://doi.org/10.1007/978-3-030-51328-3_12
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