Tracking violence in Thailand: the making of violent crime index

Chokprajakchat, Srisombat; Techagaisiyavanit, Wanaporn; Mulaphong, Dhanakorn; Iyavarakul, Tongyai; Kuanliang, Attapol; Laosunthorn, Chawan

doi:10.1057/s41284-023-00369-2

Cited by 1 publication

(2 citation statements)

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“…Furthermore, when the specific geolocation cannot be extracted or is unavailable, the coarse-grained location at the province level is used. Such a provincial location is extracted using PyThaiNLP's tag_provinces function 8 where it is mapped to the representative geolocation of the corresponding province using a gazetteer.…”

Section: ) Database Layermentioning

confidence: 99%

“…continue to experience a high incidence of serious crimes and accidents, leading to personal injuries and fatalities, as well as hindering economic growth [5,6,7,8]. Timely observation of the progression of crimes can be advantageous for law enforcement, policymakers, and other pertinent parties in their proactive and enduring efforts to prevent and address the root causes of these adverse incidents.…”

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confidence: 99%

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CAMELON: A System for Crime Metadata Extraction and Spatiotemporal Visualization From Online News Articles

Pongpaichet,

Sukosit,

Duangtanawat

et al. 2024

IEEE Access

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Crimes result in not only loss to individuals but also hinder national economic growth. While crime rates have been reported to decrease in developed countries, underdeveloped and developing nations still suffer from prevalent crimes, especially those undergoing rapid expansion of urbanization. The ability to monitor and assess trends of different types of crimes at both regional and national levels could assist local police and national-level policymakers in proactively devising means to prevent and address the root causes of criminal incidents. Furthermore, such a system could prove useful to individuals seeking to evaluate criminal activity for purposes of travel, investment, and relocation decisions. Recent literature has opted for utilizing online news articles as a reliable and timely source for crime activity information. However, most of the crime monitoring systems fueled by such news sources merely classified crimes into different types and visualized individual crimes on the map using extracted geolocations, lacking crucial information for stakeholders to make relevant, informed decisions. To better serve the unique needs of the target user groups, this paper proposes a novel comprehensive crime visualization system that mines relevant information from large-scale online news articles. The system features automatic crime-type classification and metadata extraction from news articles. The crime classification and metadata schemes are designed to serve the need for information from law enforcement and policymakers, as well as general users. Novel interactive spatiotemporal designs are integrated into the system with the ability to assess the severity and intensity of crimes in each region through the novel Criminometer index. The system is designed to be generalized for implementation in different countries with diverse prevalent crime types and languages composing the news articles, owing to the use of deep learning cross-lingual language models. The experiment results reveal that the proposed system yielded 86%, 51%, and 67% F1 in crime type classification, metadata extraction, and closed-form metadata extraction tasks, respectively. Additionally, the results of the system usability tests indicated a notable level of contentment among the target user groups. The findings not only offer insights into the possible applications of interactive spatiotemporal crime visualization tools for proactive policymaking and predictive policing but also serve as a foundation for future research that utilizes online news articles for intelligent monitoring of real-world phenomena.

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Section: ) Database Layermentioning

confidence: 99%

mentioning

confidence: 99%