Crime alert! crime typification in news based on text mining

H. Alatrista-Salas; J. Morzán-Samamé; M. Nunez-del-Prado

doi:10.1007/978-3-030-12388-8_50

Crime alert! crime typification in news based on text mining

H. Alatrista-Salas, J. Morzán-Samamé, M. Nunez-del-Prado

Universidad del Pacífico

Producción científica: Capítulo del libro/informe/acta de congreso › Capítulo de libro

5 Citas (Scopus)

Resumen

In this paper we detailed a multinomial classification-based methodology that combines different algorithms (SVM and MLP) with document representations (Tf Idf vectorization and Doc2vec embedding) and: (i) can distinguish between crime-related news and not-crime related news and; (ii) allows the assignment of each crime-related news to its corresponding crime type. With a F1-score of 84% achieved by the MLP with Doc2vec approach, it can be concluded that it is possible to answer the question of how the crimes are committed (what types of crime are perpetrated) and, in this way, offer a thermometer to citizens about criminal activity in a given territory, as reported by news articles.

Idioma original	Inglés
Título de la publicación alojada	Lecture Notes in Networks and Systems
Subtítulo de la publicación alojada	Proceedings of the 2019 Future of Information and Communication Conference
Editores	Kohei Arai, Rahul Bhatia
Lugar de publicación	Cham
Editorial	Springer Verlag
Páginas	725-741
Número de páginas	17
ISBN (versión digital)	9783030123888
ISBN (versión impresa)	9783030123871
DOI	https://doi.org/10.1007/978-3-030-12388-8_50
Estado	Publicada - 2020

Serie de la publicación

Nombre	Lecture Notes in Networks and Systems
Volumen	69

Nota bibliográfica

Publisher Copyright:
© Springer Nature Switzerland AG 2020.

ODS de las Naciones Unidas

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10.1007/978-3-030-12388-8_50

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Alatrista-Salas, H., Morzán-Samamé, J., & Nunez-del-Prado, M. (2020). Crime alert! crime typification in news based on text mining. En K. Arai, & R. Bhatia (Eds.), Lecture Notes in Networks and Systems: Proceedings of the 2019 Future of Information and Communication Conference (pp. 725-741). (Lecture Notes in Networks and Systems; Vol. 69). Springer Verlag. https://doi.org/10.1007/978-3-030-12388-8_50

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Alatrista-Salas, H, Morzán-Samamé, J & Nunez-del-Prado, M 2020, Crime alert! crime typification in news based on text mining. En K Arai & R Bhatia (eds.), Lecture Notes in Networks and Systems: Proceedings of the 2019 Future of Information and Communication Conference . Lecture Notes in Networks and Systems, vol. 69, Springer Verlag, Cham, pp. 725-741. https://doi.org/10.1007/978-3-030-12388-8_50

Crime alert! crime typification in news based on text mining. / Alatrista-Salas, H.; Morzán-Samamé, J.; Nunez-del-Prado, M.
Lecture Notes in Networks and Systems: Proceedings of the 2019 Future of Information and Communication Conference . ed. / Kohei Arai; Rahul Bhatia. Cham: Springer Verlag, 2020. p. 725-741 (Lecture Notes in Networks and Systems; Vol. 69).

Producción científica: Capítulo del libro/informe/acta de congreso › Capítulo de libro

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N1 - Publisher Copyright: © Springer Nature Switzerland AG 2020.

PY - 2020

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AB - In this paper we detailed a multinomial classification-based methodology that combines different algorithms (SVM and MLP) with document representations (Tf Idf vectorization and Doc2vec embedding) and: (i) can distinguish between crime-related news and not-crime related news and; (ii) allows the assignment of each crime-related news to its corresponding crime type. With a F1-score of 84% achieved by the MLP with Doc2vec approach, it can be concluded that it is possible to answer the question of how the crimes are committed (what types of crime are perpetrated) and, in this way, offer a thermometer to citizens about criminal activity in a given territory, as reported by news articles.

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Alatrista-Salas H, Morzán-Samamé J, Nunez-del-Prado M. Crime alert! crime typification in news based on text mining. En Arai K, Bhatia R, editores, Lecture Notes in Networks and Systems: Proceedings of the 2019 Future of Information and Communication Conference . Cham: Springer Verlag. 2020. p. 725-741. (Lecture Notes in Networks and Systems). doi: 10.1007/978-3-030-12388-8_50

Crime alert! crime typification in news based on text mining

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