Convergence of Time-Series Analytics and Social Media Intelligence: Next-Generation Infrastructure Protection Systems
A special issue of Information (ISSN 2078-2489). This special issue belongs to the section "Information Applications".
Deadline for manuscript submissions: 30 June 2026 | Viewed by 35
Special Issue Editors
Interests: knowledge-based systems; complex control systems; learning structures; information society technologies
Interests: machine learning; kernel methods; lustering; intrinsic dimension estimation; gesture recognition; handwriting recognition; time series prediction; dimensionality reduction
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The dynamics of all spheres of life of modern society are reflected in the rapid penetration of artificial intelligence (AI) into all forms of digitized systems and services. This includes organizational, social, economic, and governmental fields, revolutionizing the way in which information is processed and decisions are made. Time series in numerical or symbolic form provide information that can be analysed via artificial intelligence and machine learning (ML) algorithms to generate and test predictive models. By conducting systematic research and experiments, it is possible to optimize and improve the performances of these predictive models. This involves exploring new approaches for studying time-series data, as well as developing methodologies for their application in various practical contexts. The focus is on testing the capabilities of predictive models in real-world scenarios, while also considering the risks associated with cybersecurity.
This study of the application of predictive models for social media intelligence in the context of infrastructure protection systems will show the potential risks and benefits of their use in this area, examining the possibilities for preventing malicious actions through effective methods for detecting and neutralizing threats.
This Special Issue accepts interdisciplinary articles that address synergy between methods for time-series analysis, AI, and ML to foster innovation, efficiency, and sustainability, having been launched in response to the need to develop intelligent, adaptive systems.
Prof. Dr. Tatiana Atanasova
Dr. Francesco Camastra
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Information is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- artificial intelligence
- time-series analysis
- anomaly detection
- sentiment analysis
- classification algorithms
- machine learning
- social media intelligence
- cybersecurity
Benefits of Publishing in a Special Issue
- Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
- Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
- Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
- External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
- Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.
Further information on MDPI's Special Issue policies can be found here.
