Big Data and Social Media Intelligence

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".

Deadline for manuscript submissions: closed (30 September 2021) | Viewed by 1101

Special Issue Editor


E-Mail Website
Guest Editor
Institute for Informatics and Telematics (IIT) of the National Research Council of Italy (CNR), 56124 Pisa, Italy
Interests: big data; web mining; social network analysis; visual analytics within the context of open-source intelligence

Special Issue Information

Dear Colleagues,

The spread of low-quality information by means of social media can influence public perception regarding important topics such as politics, health, or climate change. Sometimes these disinformation activities are carried out by groups of coordinated accounts that pollute social debate with a massive number of targeted messages. All these issues contribute to transforming social media into a fertile ground for manipulation attempts. The huge amount of data produced by interactions of people requires the use of sophisticated processing and analysis techniques in order to produce information for intelligence purposes. Recent studies have highlighted the importance of exploring, studying, and modeling large amounts of data in order to discover patterns or relationships and translate them into valuable information.

In this Special Issue, we invite authors to submit original research articles related to recent advances at all levels of the applications and technologies of big data and cyber intelligence. We are particularly interested in presenting emerging technologies related to machine learning and deep learning that may have a significant impact on this research field.

Topics of interest include (but are not limited to) the following:

  • Machine learning-based detection techniques to contrast malicious activities;
  • Network analysis techniques for the characterization and detection of anomalous behaviors;
  • The detection of coordinated inauthentic behaviors;
  • Techniques for identifying information polarization on social media;
  • Investigating the dynamics of the diffusion of disinformation;
  • Text mining and graph mining for open-source intelligence;
  • Social network analysis of large networks;
  • Detection of DeepFake texts, images, and videos;
  • Fake news and hoax detection
  • The detection and characterization of information operations.

Dr. Maurizio Tesconi
Guest Editor

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. Applied Sciences is an international peer-reviewed open access semimonthly 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 2400 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.

Published Papers

There is no accepted submissions to this special issue at this moment.
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