Special Issue "Theory and Applications of Web 3.0 in the Media Sector"

A special issue of Future Internet (ISSN 1999-5903). This special issue belongs to the section "Big Data and Augmented Intelligence".

Deadline for manuscript submissions: closed (31 December 2021).

Special Issue Editors

Prof. Dr. Andreas Veglis
E-Mail Website
Guest Editor
School of Journalism and Mass Communications, Aristotle University of Thessaloniki, Thessaloniki, Greece
Interests: information technology in journalism; new media; course support environments; data journalism; open data; distance learning; content verification
Special Issues, Collections and Topics in MDPI journals
Dr. Charalampos Dimoulas
E-Mail Website
Guest Editor
Multidisciplinary Media and Mediated Communication (M3C) research group, School of Journalism & Mass Communications, Aristotle University of Thessaloniki, 541 24 Thessaloniki, Greece
Interests: media technologies; signal processing; machine learning; media authentication; audiovisual content management; multimedia semantics; semantic web
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In today’s exploding Web landscape, where vast amounts of information (documents, images, audio, videos, etc.) are produced every day from various sources across the world, professional journalists often find it difficult to retrieve specific and detailed information or form a comprehensive view about a complicated topic. This occurs because most of the content today is published in an unregulated way, and they have to navigate a network of unstructured interconnected forms of data. The lack of an efficient infrastructure in which they could easily discover, acquire, and analyze the information needed limits the exploitation prospects. The solution to this problem can be given by the advancement of Web 3.0 or Semantic Web (SW).

Web 3.0 stands as the physical extension of the current Web, in which information is given well-defined meaning, better enabling computers and people to work in cooperation. It can be seen as an Internet service with advanced technological features, in which proper/standardized documentation and semantic tagging of all content will be delivered semi-autonomously, with the help of algorithms. These features attempt to form a Web environment in which both humans and machines will understand and interpret the Web information in the same way. The technologies that support this attempt form the so-called SW services, and their role is 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 semantics and its relations with the others, i.e., fully clarified and structured. Such content will be used by computers not only for display purposes but also for interoperability and integration between systems and applications. Thus, journalists will be able to discover, integrate, and reuse pieces of information from various sources efficiently. Overall, the interconnection of concepts rather than just documents will be feasible. This is the point where the Journalism and News industry intersects with Web 3.0, towards the transition to Journalism 3.0 Within this concept, enhanced cooperation between humans and machines is taking place, and well-established journalistic practices/workflows are challenged by more sophisticated semantically-enhanced procedures. As a result, Journalism is led to a higher functional level, unlocking various capabilities of data exploitation provided by an advanced technological framework.

This Special Issue is soliciting theoretical and case study contributions, discussing and treating challenges, state-of-the-art, and solutions on Web 3.0 application in the media sector, including but not limited to: Theory of Web 3.0 in relation with media organizations, application of Web 3.0 in the media sector, Journalism 3.0 practices and procedures, semantically enhanced news validation and management, etc.

Prof. Andreas Veglis
Dr. Charalampos Dimoulas
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 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. 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 1400 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

  • Web 3.0
  • Semantic Web
  • Structured Data
  • Media industry
  • Journalistic workflow
  • Journalistic practices
  • Journalism 3.0

Published Papers (5 papers)

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Research

Article
A Semantic Preprocessing Framework for Breaking News Detection to Support Future Drone Journalism Services
Future Internet 2022, 14(1), 26; https://doi.org/10.3390/fi14010026 - 10 Jan 2022
Viewed by 140
Abstract
Nowadays, news coverage implies the existence of video footage and sound, from which arises the need for fast reflexes by media organizations. Social media and mobile journalists assist in fulfilling this requirement, but quick on-site presence is not always feasible. In the past [...] Read more.
Nowadays, news coverage implies the existence of video footage and sound, from which arises the need for fast reflexes by media organizations. Social media and mobile journalists assist in fulfilling this requirement, but quick on-site presence is not always feasible. In the past few years, Unmanned Aerial Vehicles (UAVs), and specifically drones, have evolved to accessible recreational and business tools. Drones could help journalists and news organizations capture and share breaking news stories. Media corporations and individual professionals are waiting for the appropriate flight regulation and data handling framework to enable their usage to become widespread. Drone journalism services upgrade the usage of drones in day-to-day news reporting operations, offering multiple benefits. This paper proposes a system for operating an individual drone or a set of drones, aiming to mediate real-time breaking news coverage. Apart from the definition of the system requirements and the architecture design of the whole system, the current work focuses on data retrieval and the semantics preprocessing framework that will be the basis of the final implementation. The ultimate goal of this project is to implement a whole system that will utilize data retrieved from news media organizations, social media, and mobile journalists to provide alerts, geolocation inference, and flight planning. Full article
(This article belongs to the Special Issue Theory and Applications of Web 3.0 in the Media Sector)
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Article
An AI-Enabled Framework for Real-Time Generation of News Articles Based on Big EO Data for Disaster Reporting
Future Internet 2021, 13(6), 161; https://doi.org/10.3390/fi13060161 - 19 Jun 2021
Viewed by 733
Abstract
In the field of journalism, the collection and processing of information from different heterogeneous sources are difficult and time-consuming processes. In the context of the theory of journalism 3.0, where multimedia data can be extracted from different sources on the web, the possibility [...] Read more.
In the field of journalism, the collection and processing of information from different heterogeneous sources are difficult and time-consuming processes. In the context of the theory of journalism 3.0, where multimedia data can be extracted from different sources on the web, the possibility of creating a tool for the exploitation of Earth observation (EO) data, especially images by professionals belonging to the field of journalism, is explored. With the production of massive volumes of EO image data, the problem of their exploitation and dissemination to the public, specifically, by professionals in the media industry, arises. In particular, the exploitation of satellite image data from existing tools is difficult for professionals who are not familiar with image processing. In this scope, this article presents a new innovative platform that automates some of the journalistic practices. This platform includes several mechanisms allowing users to early detect and receive information about breaking news in real-time, retrieve EO Sentinel-2 images upon request for a certain event, and automatically generate a personalized article according to the writing style of the author. Through this platform, the journalists or editors can also make any modifications to the generated article before publishing. This platform is an added-value tool not only for journalists and the media industry but also for freelancers and article writers who use information extracted from EO data in their articles. Full article
(This article belongs to the Special Issue Theory and Applications of Web 3.0 in the Media Sector)
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Article
From Rigidity to Exuberance: Evolution of News on Online Newspaper Homepages
Future Internet 2021, 13(6), 150; https://doi.org/10.3390/fi13060150 - 09 Jun 2021
Viewed by 1071
Abstract
Since their emergence in the mid-90s, online media have evolved from simple digital editions that merely served to dump content from print newspapers, to sophisticated multi-format products with multimedia and interactive features. In order to discover their visual evolution, this article conducts a [...] Read more.
Since their emergence in the mid-90s, online media have evolved from simple digital editions that merely served to dump content from print newspapers, to sophisticated multi-format products with multimedia and interactive features. In order to discover their visual evolution, this article conducts a longitudinal study of the design of online media by analyzing the front pages of five general-information Spanish newspapers (elpais.com, elmundo.es, abc.es, lavanguardia.com, and elperiodico.com) over the past 25 years (1996–2020). Moreover, some of their current features are listed. To this end, six in-depth interviews were conducted with managers of different online media outlets. The results indicate that the media analysed have evolved from a static, rigid format, to a dynamic, mobile, and multi-format model. Regarding the language used, along with increased multimedia and interactive possibilities, Spanish online media currently display a balance between text and images on their front pages. Lastly, audience information consumption habits, largely superficial and sporadic, and the increasing technification and speed of production processes, means that news media have lost in terms of the design part of the individual personality they had in their print editions. However, they maintain their index-type front pages as one of their most characteristic elements, which are very vertical and highly saturated. Full article
(This article belongs to the Special Issue Theory and Applications of Web 3.0 in the Media Sector)
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Article
An AI-Enabled Stock Prediction Platform Combining News and Social Sensing with Financial Statements
Future Internet 2021, 13(6), 138; https://doi.org/10.3390/fi13060138 - 21 May 2021
Viewed by 983
Abstract
In recent years, the area of financial forecasting has attracted high interest due to the emergence of huge data volumes (big data) and the advent of more powerful modeling techniques such as deep learning. To generate the financial forecasts, systems are developed that [...] Read more.
In recent years, the area of financial forecasting has attracted high interest due to the emergence of huge data volumes (big data) and the advent of more powerful modeling techniques such as deep learning. To generate the financial forecasts, systems are developed that combine methods from various scientific fields, such as information retrieval, natural language processing and deep learning. In this paper, we present ASPENDYS, a supportive platform for investors that combines various methods from the aforementioned scientific fields aiming to facilitate the management and the decision making of investment actions through personalized recommendations. To accomplish that, the system takes into account both financial data and textual data from news websites and the social networks Twitter and Stocktwits. The financial data are processed using methods of technical analysis and machine learning, while the textual data are analyzed regarding their reliability and then their sentiments towards an investment. As an outcome, investment signals are generated based on the financial data analysis and the sensing of the general sentiment towards a certain investment and are finally recommended to the investors. Full article
(This article belongs to the Special Issue Theory and Applications of Web 3.0 in the Media Sector)
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Article
A Web Interface for Analyzing Hate Speech
Future Internet 2021, 13(3), 80; https://doi.org/10.3390/fi13030080 - 22 Mar 2021
Cited by 2 | Viewed by 1439
Abstract
Social media services make it possible for an increasing number of people to express their opinion publicly. In this context, large amounts of hateful comments are published daily. The PHARM project aims at monitoring and modeling hate speech against refugees and migrants in [...] Read more.
Social media services make it possible for an increasing number of people to express their opinion publicly. In this context, large amounts of hateful comments are published daily. The PHARM project aims at monitoring and modeling hate speech against refugees and migrants in Greece, Italy, and Spain. In this direction, a web interface for the creation and the query of a multi-source database containing hate speech-related content is implemented and evaluated. The selected sources include Twitter, YouTube, and Facebook comments and posts, as well as comments and articles from a selected list of websites. The interface allows users to search in the existing database, scrape social media using keywords, annotate records through a dedicated platform and contribute new content to the database. Furthermore, the functionality for hate speech detection and sentiment analysis of texts is provided, making use of novel methods and machine learning models. The interface can be accessed online with a graphical user interface compatible with modern internet browsers. For the evaluation of the interface, a multifactor questionnaire was formulated, targeting to record the users’ opinions about the web interface and the corresponding functionality. Full article
(This article belongs to the Special Issue Theory and Applications of Web 3.0 in the Media Sector)
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