Evolution of Mathematical Theories in Applied Statistics
A special issue of Axioms (ISSN 2075-1680).
Deadline for manuscript submissions: 20 February 2026 | Viewed by 103
Special Issue Editor
2. Graduate Program in Political Science, Federal University of Pernambuco, Recife 52070-040, Brazil
Interests: probability; theory of new distributions; temporal series and NLP
Special Issue Information
Dear Colleagues,
Advances in studies using unstructured data have been noted in the academic community in recent years. Machine Learning, Sentiment Analysis, Natural Language Processing models, and Data Envelopment Analysis, for example, are being used in various fields of knowledge, such as healthcare, engineering, and statistics.
With the proliferation of various social networks, the amount of unstructured data has been growing rapidly, along with the need for its analysis, especially after the COVID-19 pandemic. The social distancing measures in effect at the time caused communication between people to become online: via email, phone calls, and messages on social networks like Instagram, WhatsApp, and X (formerly Twitter), further expanding the existing base of unstructured data.
The scope of this Special Issue focuses on (but is not limited to) the following contexts:
- New models of supervised and unsupervised classification;
- Social networks analysis and its applications in several areas;
- Development of new centrality metrics in complex networks;
- Graph theory versus complex networks. Thinking about real applications, the use of classical graph theory is not ideal for the study of complex networks since the former is generally homogeneous and the latter is dynamic, for example;
- Theory of multiple relationships in networks. That is, theory for multilayer (interacting) networks.
Dr. Maria do Carmo Soares de Lima
Guest Editor
Manuscript Submission Information
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Keywords
- mathematical statistics
- applied statistics
- machine learning
- statistical models
- statistical analysis
- data analysis
- natural language processing
- regression models
- data envelopment analysis
- graph theory
- complex network
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