# Theory and Applications of Web 3.0 in the Media Sector
###### Abstract  
We live in a digital era, with vast technological advancements, which, among others, have a major impact on the media domain. More specifically, progress in the last two decades led to the end-to-end digitalization of the media industry, resulting in a rapidly evolving media landscape. In addition to news digitization, User-Generated Content (UGC) is dominant in this new environment, also fueled by Social Media, which has become commonplace for news publishing, propagation, consumption, and interactions. However, the exponential increase in produced and distributed content, with the multiplied growth in the number of plenary individuals involved in the processes, created urgent needs and challenges that need careful treatment. Hence, intelligent processing and automation incorporated into the Semantic Web vision, also known as Web 3.0, aim at providing sophisticated data documentation, retrieval, and management solutions to meet the demands of the new digital world. Specifically, for the sensitive news and media domains, necessities are created both at the production and consumption ends, dealing with content production and validation, as well as tools empowering and engaging audiences (professionals and end users). In this direction, state-of-the-art works studying news detection, modeling, generation, recommendation, evaluation, and utilization are included in the current Special Issue, enlightening multiple contemporary journalistic practices and media perspectives. web 3.0; semantic web; media industry; journalistic practices; journalism 3.0; news semantics; news recommendation; media automations; disinformation; hate speech +
Footnote †: journal: _Future Internet_  
everyday practice for thousands of people, offering simplicity, immediacy, and interactivity [1; 2; 3; 4; 12]. Furthermore, the proliferation of mobile devices (smartphones, tablets, etc.) and their inherent content-capturing and networking capabilities fueled citizen and participatory journalism paradigms, enabling plenary users to contribute User-Generated Content (UGC) fast and effortlessly (i.e., personal or public information, such as news events/stories, articles, opinions, comments, etc.) [1; 9; 10; 11; 12; 13; 14]. At the same time, the plurality of data and news streams created urgent needs for better content documentation, validation, and management [1; 4; 9; 10; 11; 12; 13; 14]. Hence, the advancement of the Semantic Web (SW) or Web 3.0 has been envisioned as a sophisticated solution to the above problems and challenges aspiring intelligent multimedia processing, analysis, and creation techniques [4; 9; 10; 16]. Web 3.0 stands as the physical extension of the current Web where information is given a well-defined meaning, better enabling computers and people to work in cooperation [4; 9; 10; 11; 12; 13; 14]. Therefore, it can be seen as an Internet service with sophisticated technological features, in which proper/standardized documentation and semantic tagging will be delivered with the help of algorithms (in fully or semi-automated processes) [4; 9; 10]. These features attempt to form a Web environment in which humans and machines understand and interpret web-streamed information in the same context. The so-called SW services embody and integrate technologies aiming to complete the transition from today's Web of documents to a Web of well-documented data, where every piece of information will be accompanied by its semantic, conceptual, and contextual metadata. Fully structured and clarified relations to others (users, events, stories, models, etc.) will expedite data visualization and display purposes, also facilitating interoperability and integration between systems, environments, and applications, interconnecting concepts rather than just documents [4; 9; 10; 16; 17; 18; 4; 19]. Thus, journalists and plenary individuals (content contributors and news consumers) will be able to efficiently discover, integrate, and reuse pieces of information from various sources.