Assessing Opinions on Software as a Weapon in the Context of (Inter)national Security

Silomon, Jantje A. M.; Roeling, Mark Patrick

doi:10.1007/978-3-662-56672-5_4

Cited by 1 publication

(1 citation statement)

References 15 publications

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“…Machine learning techniques are recurrent among the methodological sets found in the selected literature, as observed in the previously listed works. Nonetheless, other groups of methods were recommended for further research developments, such as multicriteria methods for decision support in planning activities for criminal combat [30]; social network analysis to find hidden patterns of illegal activities [84]; traditional statistical methods to support the analysis of opinions about security threats using information collected via questionnaires [98]; bio-inspired algorithms to simulate security threats or risks [97]; the combination of graphs and neural networks to assist in answering key investigation questions [99].…”

Section: Methodological Extensionsmentioning

confidence: 99%

Enabling Public Security Text-Based Analytics: A Survey to Outline Research Directions

De Carvalho,

Dos Santos,

Nepomuceno

et al. 2024

Preprint

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Text mining is a technological trend often highlighted in the continuous exchange of information through interconnected media. Its applicability goes beyond private organizations, as the public sector also requires it to treat textual information regarding services offered. Within this scenario, public security emerges as a prominent user of text mining that seeks to ensure the construction of data and knowledgebases to support decision-making about law enforcement actions to ensure citizen welfare. The primary objectives of this article are: (i) to develop a survey to identify text mining applications, techniques, opportunities, and challenges in public security, and (ii) to outline research directions concerning these topics and provide insights so that interested researchers can develop new studies. The literature was searched within four databases: Scopus, IEEE Xplore, ACM Digital Library, and Web of Science. A filtering process was applied to extract the works most aligned with the target theme, resulting in the selection of 194 of the most relevant works for a literature review. There were identified nineteen key applications of text mining related to public security and the most recurrent techniques and technologies reported between 2014 to 2021, supporting outlining three axes for future directions: one with possible expansion of objectives for new research; another on changes and adaptations in scopes for the methodological context; and the last one on expansions and changes in application scenarios based on the literature.

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