Information Communication Technologies and Social Media

A special issue of Future Internet (ISSN 1999-5903). This special issue belongs to the section "Smart System Infrastructure and Applications".

Deadline for manuscript submissions: 31 March 2025 | Viewed by 299

Special Issue Editors


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Guest Editor
School of Computer Science (National Pilot Software Engineering School), Beijing University of Posts and Telecommunications, Beijing 100084, China
Interests: social media and data mining; artificial intelligence and applications; recommendation systems; deep learning
School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing 100876, China
Interests: artificial intelligence and applications; vision and language
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
College of Information Science and Technology and College of Cyber Security, Jinan University, Guangzhou 510632, China
Interests: algorithm optimization in artificial intelligence

Special Issue Information

Dear Colleagues,

Information Communication Technologies (ICTs) and social media have revolutionized the way we connect, communicate, and share information. The proliferation of smartphones, high-speed internet, and various online platforms has facilitated unprecedented levels of interaction and content creation. Social media platforms like Facebook, Twitter, and Instagram enable individuals to share personal updates, engage in public discourse, and participate in global communities.

These technologies offer numerous benefits, such as enhancing social connections, fostering community building, and enabling real-time information sharing. Social media has become a powerful tool for marketing, activism, and entertainment, providing a platform for voices that might otherwise go unheard.

However, the rapid growth of ICTs and social media also presents significant challenges. Issues such as data privacy, misinformation, cyberbullying, and digital addiction have emerged as critical concerns. Social media platforms often collect vast amounts of personal data, raising questions about user consent and data security. The spread of false information can influence public opinion and disrupt societal harmony.

The aim of this Special Issue is to explore the latest advancements and challenges in ICTs and social media. We welcome contributions that address both theoretical and practical aspects, as well as interdisciplinary approaches.

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

  • Privacy and security issues in social media platforms;
  • The role of ICTs in digital inclusion and access to information;
  • Innovations in social media algorithms and user experience;
  • Data analytics and insights from social media interactions;
  • Approaches to enhance user privacy and data protection on social media.

We invite researchers and practitioners to submit their work to contribute to a deeper understanding of the transformative effects of ICTs and social media on society.

Dr. Jinpeng Chen
Dr. Ruifan Li
Dr. Kaimin Wei
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. Future Internet 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 1600 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

  • social media impact
  • data privacy and security
  • digital communication
  • misinformation and media literacy
  • digital inclusion
  • cyberbullying and online safety
  • user behavior analytics
  • social media algorithms
  • ethical considerations in ICT
  • digital addiction effects

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Published Papers (1 paper)

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Research

25 pages, 622 KiB  
Article
Cross-Domain Fake News Detection Through Fusion of Evidence from Multiple Social Media Platforms
by Jannatul Ferdush, Joarder Kamruzzaman, Gour Karmakar, Iqbal Gondal and Rajkumar Das
Future Internet 2025, 17(2), 61; https://doi.org/10.3390/fi17020061 (registering DOI) - 3 Feb 2025
Abstract
Fake news has become a significant challenge on online social platforms, increasing uncertainty and unwanted tension in society. The negative impact of fake news on political processes, public health, and social harmony underscores the urgency of developing more effective detection systems. Existing methods [...] Read more.
Fake news has become a significant challenge on online social platforms, increasing uncertainty and unwanted tension in society. The negative impact of fake news on political processes, public health, and social harmony underscores the urgency of developing more effective detection systems. Existing methods for fake news detection often focus solely on one platform, potentially missing important clues that arise from multiple platforms. Another important consideration is that the domain of fake news changes rapidly, making cross-domain analysis more difficult than in-domain analysis. To address both of these limitations, our method takes evidence from multiple social media platforms, enhances our cross-domain analysis, and improves overall detection accuracy. Our method employs the Dempster–Shafer combination rule for aggregating probabilities for comments being fake from two different social media platforms. Instead of directly using the comments as features, our approach improves fake news detection by examining the relationships and calculating correlations among comments from different platforms. This provides a more comprehensive view of how fake news spreads and how users respond to it. Most importantly, our study reveals that true news is typically rich in content, while fake news tends to generate a vast thread of comments. Therefore, we propose a combined method that merges content- and comment-based approaches, allowing our model to identify fake news with greater accuracy and showing an overall improvement of 7% over previous methods. Full article
(This article belongs to the Special Issue Information Communication Technologies and Social Media)
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