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Future Internet
Special Issues
Information Communication Technologies and Social Media
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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: 20 November 2025 | Viewed by 2849

Special Issue Editors

Dr. Jinpeng Chen

E-Mail Website
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
Dr. Ruifan Li

E-Mail Website
Guest Editor
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
Dr. Kaimin Wei

E-Mail Website
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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  • 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.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue policies can be found here.

Published Papers (3 papers)

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22 pages, 2061 KiB  
Article
Knowledge Sharing in Security-Sensitive Communities
by Yonit Rusho, Daphne Ruth Raban, David Simantov and Gilad Ravid
Future Internet 2025, 17(4), 144; https://doi.org/10.3390/fi17040144 - 26 Mar 2025
Viewed by 247
Abstract
Collective intelligence inherently relies on knowledge sharing. In security-sensitive organizations, tension arises between the need to develop collective knowledge and organizational culture, which requires secrecy. Drawing on the effects of trust on social behavior, this study examines knowledge-sharing in security-sensitive organizations compared to [...] Read more.
Collective intelligence inherently relies on knowledge sharing. In security-sensitive organizations, tension arises between the need to develop collective knowledge and organizational culture, which requires secrecy. Drawing on the effects of trust on social behavior, this study examines knowledge-sharing in security-sensitive organizations compared to non-sensitive organizations dealing with the same subject matter. Methodology—We use Social Network Analysis (SNA) to analyze data from 18 communities: 7 security-sensitive and 9 non-sensitive. This comparative analysis explores the impact of organizational culture on communication structures and knowledge-sharing patterns. Findings—(1) The communication structure of security-sensitive communities differs from the structure of non-sensitive communities; (2) Security-sensitive communities have a higher density than non-sensitive communities. (3) When two security-sensitive organizations join together, knowledge sharing decreases. (4) Characteristics of the organizational culture of security-sensitive communities affect their network structure, which in turn affects knowledge sharing. This study provides valuable insights into the complex relationship between organizational culture, trust, and knowledge sharing in security-sensitive contexts. It highlights how secrecy and trust dynamics shape communication patterns and collective intelligence, contributing to a deeper understanding of knowledge-sharing practices in environments where security concerns are paramount. The findings are particularly relevant for improving knowledge-sharing strategies in both security-sensitive and non-sensitive organizations. Full article
(This article belongs to the Special Issue Information Communication Technologies and Social Media)
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22 pages, 601 KiB  
Article
University Students’ Subjective Well-Being in Japan Between 2021 and 2023: Its Relationship with Social Media Use
by Shaoyu Ye and Kevin K. W. Ho
Future Internet 2025, 17(3), 126; https://doi.org/10.3390/fi17030126 - 12 Mar 2025
Viewed by 826
Abstract
This study investigated whether young adults’ social media use and subjective well-being (SWB) changed during the COVID-19 pandemic. It examined the possible relationships between social media use, SWB, and personality traits. It included generalized trust, self-consciousness, friendship, and desire for self-presentation and admiration, [...] Read more.
This study investigated whether young adults’ social media use and subjective well-being (SWB) changed during the COVID-19 pandemic. It examined the possible relationships between social media use, SWB, and personality traits. It included generalized trust, self-consciousness, friendship, and desire for self-presentation and admiration, in relation to different patterns of social media use and genders. Data were collected from university students in Japan from 2021 to 2023 and were analyzed based on different social media use patterns. The conceptual model was based on the cognitive bias and social network mediation models. Data were analyzed using ANOVA and regression analyses. The findings revealed that, over time, young adults’ anxiety toward COVID-19 decreased, while their SWB improved and their social support increased. Depression tendencies showed a negative association, whereas social support was positively related to improvement of SWB for all three patterns of social media use. Furthermore, online communication skills had a positive relationship with improvements in students’ SWB in Patterns 1 (LINE + Twitter + Instagram) and 2 (LINE + Twitter + Instagram + TikTok). The self-indeterminate factor had a positive relationship with students’ SWB for all patterns in 2022 and 2023, and the praise acquisition factor had a positive relationship with improvements in students’ SWB in Patterns 1 and 2. These results suggest that young adults maintained their mental health through different social media usage patterns, considering their personality traits and social situations associated with COVID-19. Particularly, receiving social support, decreasing people’s depression tendencies, and displaying different aspects of the “self” online can improve SWB. This study elucidates the mental health situations of university students in Japan and will help public health authorities develop new support programs that help digital natives improve their mental health in the context of social environmental changes. Full article
(This article belongs to the Special Issue Information Communication Technologies and Social Media)
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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 - 3 Feb 2025
Viewed by 1279
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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