Proceedings of the 2022 3rd International Conference on Big Data and Social Sciences (ICBDSS 2022)

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Research on Situational Prevention of Drug Crimes from the Perspective of Big Data Based on SPSS Software

Authors
Cheng Bo1, 2, *
1Law School, Academy of Marxism, Xiangtan University, Xiangtan, China
2Hunan University of Traditional Chinese Medicine, Changsha, China
*Corresponding author. Email: chengbo0610@126.com
Corresponding Author
Cheng Bo
Available Online 27 December 2022.
DOI
10.2991/978-94-6463-064-0_71How to use a DOI?
Keywords
big data; drug crimes; situational factors; crime mechanism; situational prevention
Abstract

Due to the complexity, concealment, and intelligence of drug crimes, traditional social prevention, penalty prevention and other measures are difficult to effectively deal with. The advent of the era of big data has brought opportunities for the prevention and control of drug crimes. The track, record, and analytical functions of big data can realize effective management of drug-related personnel information, which is conducive to accurately grasping the law of criminal behavior and development and establish relevant predictive models, so as to do a good job in the prevention of drug crime situations in a targeted manner. This article combines big data methods and uses SPSS software to perform data statistics, summarizes the social and physical situation factors of drug crimes, uses the relevant thinking of big data thinking, comprehensively analyzes the situation factors, and summarizes the mechanism of the situational factors of drug crimes and constructs crime prediction model; in view of this, a drug crime situation prevention strategy based on big data technology is proposed, and a drug crime situation prevention model is constructed to improve the pertinence and accuracy of drug crime situation prevention.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2022 3rd International Conference on Big Data and Social Sciences (ICBDSS 2022)
Series
Atlantis Highlights in Computer Sciences
Publication Date
27 December 2022
ISBN
10.2991/978-94-6463-064-0_71
ISSN
2589-4900
DOI
10.2991/978-94-6463-064-0_71How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Cheng Bo
PY  - 2022
DA  - 2022/12/27
TI  - Research on Situational Prevention of Drug Crimes from the Perspective of Big Data Based on SPSS Software
BT  - Proceedings of the 2022 3rd International Conference on Big Data and Social Sciences (ICBDSS 2022)
PB  - Atlantis Press
SP  - 691
EP  - 699
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-064-0_71
DO  - 10.2991/978-94-6463-064-0_71
ID  - Bo2022
ER  -