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IJ-PAIA 2021 : a special issue of Information journal (ISSN 2078-2489) on Predictive Analytics and Illicit Activities


When N/A
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Submission Deadline May 31, 2021
Categories    artificial intelligence   NLP

Call For Papers

Call for papers : a special issue of Information journal (ISSN 2078-2489)
"Predictive Analytics and Illicit Activities"

Deadline for manuscript submissions: 31 May 2021.

This Special Issue focuses on the use of advanced techniques to mine and exploit heterogeneous digital data on illicit activities for descriptive or predictive analyses.

Digital technologies as well as digital information and communication networks facilitate illicit activities such as illicit financial flows, illicit art and drug markets, forbidden posts and comments on social media, and recruitment or incitement of illicit activities such as any form of radicalization, etc. New models, methods and tools need to be developed to prevent, detect or warn, and possibly mitigate or hinder these illicit actions.

These methods encompass machine learning or data mining models as well as visualization models to help in detecting or mitigating possible illicit activities.

This Special Issue aims to gather both research papers reporting new scientific results and technical papers reporting project results, demos/prototypes/tools.

This Special Issue invites submissions covering, but not limited to, the following topics:

- Crime detection and investigation;
- Risk analysis;
- Misinformation and misbehavior analysis and detection;
- Trend detection, analysis and tracking;
- Weak signal detection;
- Information / opinion / knowledge spread and modelling;
- Information quality in social network;
- Community detection, expertise and authority discovery;
- Social influence, recommendation and media;
- Behavior analysis in social networks;
- Sentiment analysis;
- Network visualization and modeling;
- Data mining and machine learning;
- Real-world case studies;
- Ongoing projects based on social media and/or social networks;
- Ethics.

Manuscript Submission Information

Manuscripts should be submitted online at 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 papers will be 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 1000 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.


crime detection and investigation
risk analysis
misinformation and misbehavior analysis and detection
trend detection, analysis and tracking
weak signal detection
information/opinion/knowledge spread and modelling
information quality in social network
community detection
expertise and authority discovery
social influence, recommendation and media
behavior analysis in social networks
sentiment analysis
network visualization and modeling
data mining and machine learning
real-world case studies
ongoing projects based on social media and/or social networks

Invited Editor: Pr. Josiane Mothe, Univ. Toulouse

Information Journal is CiteScore 2.4, SJR 2019 0.353

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