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 (20 November 2022) | Viewed by 42659

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Special Issue Editors


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Guest Editor
Media Informatics Lab, 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; algorithmic journalism
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Guest Editor
Multidisciplinary Media and Mediated Communication (M3C) Research Group, School of Journalism & Mass Communications, Aristotle University of Thessaloniki, 54124 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

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Keywords

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

Published Papers (12 papers)

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Editorial

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10 pages, 651 KiB  
Editorial
Theory and Applications of Web 3.0 in the Media Sector
by Charalampos A. Dimoulas and Andreas Veglis
Future Internet 2023, 15(5), 165; https://doi.org/10.3390/fi15050165 - 28 Apr 2023
Cited by 1 | Viewed by 1613
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 [...] Read more.
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. Full article
(This article belongs to the Special Issue Theory and Applications of Web 3.0 in the Media Sector)
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Research

Jump to: Editorial

23 pages, 1567 KiB  
Article
Integrating Chatbot Media Automations in Professional Journalism: An Evaluation Framework
by Efthimis Kotenidis, Nikolaos Vryzas, Andreas Veglis and Charalampos Dimoulas
Future Internet 2022, 14(11), 343; https://doi.org/10.3390/fi14110343 - 21 Nov 2022
Cited by 1 | Viewed by 2093
Abstract
Interactivity has been a very sought-after feature in professional journalism ever since the media industry transitioned from print into the online space. Within this context, chatbots started to infiltrate the media sphere and provide news organizations with new and innovative ways to create [...] Read more.
Interactivity has been a very sought-after feature in professional journalism ever since the media industry transitioned from print into the online space. Within this context, chatbots started to infiltrate the media sphere and provide news organizations with new and innovative ways to create and share their content, with an even larger emphasis on back-and-forth communication and news reporting personalization. The present research highlights two important factors that can determine the efficient integration of chatbots in professional journalism: the feasibility of chatbot programming by journalists without a background in computer science using coding-free platforms and the usability of the created chatbot agents for news reporting to the audience. This paper aims to review some of the most popular, coding-free chatbot creation platforms that are available to journalists today. To that end, a three-phase evaluation framework is introduced. First off, the interactivity features that they offer to media industry workers are evaluated using an appropriate metrics framework. Secondly, a two- part workshop is conducted where journalists use the aforementioned platforms to create their own chatbot news reporting agents with minimum training, and lastly, the created chatbots are evaluated by a larger audience concerning the usability and overall user experience. Full article
(This article belongs to the Special Issue Theory and Applications of Web 3.0 in the Media Sector)
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21 pages, 2834 KiB  
Article
Modeling and Validating a News Recommender Algorithm in a Mainstream Medium-Sized News Organization: An Experimental Approach
by Paschalia (Lia) Spyridou, Constantinos Djouvas and Dimitra Milioni
Future Internet 2022, 14(10), 284; https://doi.org/10.3390/fi14100284 - 29 Sep 2022
Cited by 3 | Viewed by 2011
Abstract
News recommending systems (NRSs) are algorithmic tools that filter incoming streams of information according to the users’ preferences or point them to additional items of interest. In today’s high-choice media environment, attention shifts easily between platforms and news sites and is greatly affected [...] Read more.
News recommending systems (NRSs) are algorithmic tools that filter incoming streams of information according to the users’ preferences or point them to additional items of interest. In today’s high-choice media environment, attention shifts easily between platforms and news sites and is greatly affected by algorithmic technologies; news personalization is increasingly used by news media to woo and retain users’ attention and loyalty. The present study examines the implementation of a news recommender algorithm in a leading news media organization on the basis of observation of the recommender system’s outputs. Drawing on an experimental design employing the ‘algorithmic audit’ method, and more specifically the ‘collaborative audit’ which entails utilizing users as testers of algorithmic systems, we analyze the composition of the personalized MyNews area in terms of accuracy and user engagement. Premised on the idea of algorithms being black boxes, the study has a two-fold aim: first, to identify the implicated design parameters enlightening the underlying functionality of the algorithm, and second, to evaluate in practice the NRS through the deployed experimentation. Results suggest that although the recommender algorithm manages to discriminate between different users on the basis of their past behavior, overall, it underperforms. We find that this is related to flawed design decisions rather than technical deficiencies. The study offers insights to guide the improvement of NRSs’ design that both considers the production capabilities of the news organization and supports business goals, user demands and journalism’s civic values. Full article
(This article belongs to the Special Issue Theory and Applications of Web 3.0 in the Media Sector)
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21 pages, 5986 KiB  
Article
Aesthetic Trends and Semantic Web Adoption of Media Outlets Identified through Automated Archival Data Extraction
by Aristeidis Lamprogeorgos, Minas Pergantis, Michail Panagopoulos and Andreas Giannakoulopoulos
Future Internet 2022, 14(7), 204; https://doi.org/10.3390/fi14070204 - 30 Jun 2022
Cited by 1 | Viewed by 1887
Abstract
The last decade has been a time of great progress in the World Wide Web and this progress has manifested in multiple ways, including both the diffusion and expansion of Semantic Web technologies and the advancement of the aesthetics and usability of Web [...] Read more.
The last decade has been a time of great progress in the World Wide Web and this progress has manifested in multiple ways, including both the diffusion and expansion of Semantic Web technologies and the advancement of the aesthetics and usability of Web user interfaces. Online media outlets have often been popular Web destinations and so they are expected to be at the forefront of innovation, both in terms of the integration of new technologies and in terms of the evolution of their interfaces. In this study, various Web data extraction techniques were employed to collect current and archival data from news websites that are popular in Greece, in order to monitor and record their progress through time. This collected information, which took the form of a website’s source code and an impression of their homepage in different time instances of the last decade, has been used to identify trends concerning Semantic Web integration, DOM structure complexity, number of graphics, color usage, and more. The identified trends were analyzed and discussed with the purpose of gaining a better understanding of the ever-changing presence of the media industry on the Web. The study concluded that the introduction of Semantic Web technologies in online media outlets was rapid and extensive and that website structural and visual complexity presented a steady and significant positive trend, accompanied by increased adherence to color harmony. Full article
(This article belongs to the Special Issue Theory and Applications of Web 3.0 in the Media Sector)
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26 pages, 6231 KiB  
Article
MeVer NetworkX: Network Analysis and Visualization for Tracing Disinformation
by Olga Papadopoulou , Themistoklis Makedas , Lazaros Apostolidis , Francesco Poldi , Symeon Papadopoulos and Ioannis Kompatsiaris 
Future Internet 2022, 14(5), 147; https://doi.org/10.3390/fi14050147 - 10 May 2022
Cited by 8 | Viewed by 4945
Abstract
The proliferation of online news, especially during the “infodemic” that emerged along with the COVID-19 pandemic, has rapidly increased the risk of and, more importantly, the volume of online misinformation. Online Social Networks (OSNs), such as Facebook, Twitter, and YouTube, serve as fertile [...] Read more.
The proliferation of online news, especially during the “infodemic” that emerged along with the COVID-19 pandemic, has rapidly increased the risk of and, more importantly, the volume of online misinformation. Online Social Networks (OSNs), such as Facebook, Twitter, and YouTube, serve as fertile ground for disseminating misinformation, making the need for tools for analyzing the social web and gaining insights into communities that drive misinformation online vital. We introduce the MeVer NetworkX analysis and visualization tool, which helps users delve into social media conversations, helps users gain insights about how information propagates, and provides intuition about communities formed via interactions. The contributions of our tool lie in easy navigation through a multitude of features that provide helpful insights about the account behaviors and information propagation, provide the support of Twitter, Facebook, and Telegram graphs, and provide the modularity to integrate more platforms. The tool also provides features that highlight suspicious accounts in a graph that a user should investigate further. We collected four Twitter datasets related to COVID-19 disinformation to present the tool’s functionalities and evaluate its effectiveness. Full article
(This article belongs to the Special Issue Theory and Applications of Web 3.0 in the Media Sector)
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17 pages, 1806 KiB  
Article
A Prototype Web Application to Support Human-Centered Audiovisual Content Authentication and Crowdsourcing
by Nikolaos Vryzas, Anastasia Katsaounidou, Lazaros Vrysis, Rigas Kotsakis and Charalampos Dimoulas
Future Internet 2022, 14(3), 75; https://doi.org/10.3390/fi14030075 - 27 Feb 2022
Cited by 6 | Viewed by 2945
Abstract
Media authentication relies on the detection of inconsistencies that may indicate malicious editing in audio and video files. Traditionally, authentication processes are performed by forensics professionals using dedicated tools. There is rich research on the automation of this procedure, but the results do [...] Read more.
Media authentication relies on the detection of inconsistencies that may indicate malicious editing in audio and video files. Traditionally, authentication processes are performed by forensics professionals using dedicated tools. There is rich research on the automation of this procedure, but the results do not yet guarantee the feasibility of providing automated tools. In the current approach, a computer-supported toolbox is presented, providing online functionality for assisting technically inexperienced users (journalists or the public) to investigate visually the consistency of audio streams. Several algorithms based on previous research have been incorporated on the backend of the proposed system, including a novel CNN model that performs a Signal-to-Reverberation-Ratio (SRR) estimation with a mean square error of 2.9%. The user can access the web application online through a web browser. After providing an audio/video file or a YouTube link, the application returns as output a set of interactive visualizations that can allow the user to investigate the authenticity of the file. The visualizations are generated based on the outcomes of Digital Signal Processing and Machine Learning models. The files are stored in a database, along with their analysis results and annotation. Following a crowdsourcing methodology, users are allowed to contribute by annotating files from the dataset concerning their authenticity. The evaluation version of the web application is publicly available online. Full article
(This article belongs to the Special Issue Theory and Applications of Web 3.0 in the Media Sector)
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28 pages, 4544 KiB  
Article
Estimation on the Importance of Semantic Web Integration for Art and Culture Related Online Media Outlets
by Andreas Giannakoulopoulos, Minas Pergantis, Nikos Konstantinou, Alexandros Kouretsis, Aristeidis Lamprogeorgos and Iraklis Varlamis
Future Internet 2022, 14(2), 36; https://doi.org/10.3390/fi14020036 - 24 Jan 2022
Cited by 3 | Viewed by 2974
Abstract
Since the dawn of the new millennium and even earlier, a coordinated effort has been underway to expand the World Wide Web into a machine-readable web of data known as the Semantic Web. The field of art and culture has been one of [...] Read more.
Since the dawn of the new millennium and even earlier, a coordinated effort has been underway to expand the World Wide Web into a machine-readable web of data known as the Semantic Web. The field of art and culture has been one of the most eager to integrate with the Semantic Web, since metadata, data structures, linked-data, e.g., the Getty vocabularies project and the Europeana LOD initiative—and other building blocks of this web of data are considered essential in cataloging and disseminating art and culture-related content. However, art is a constantly evolving entity and as such it is the subject of a vast number of online media outlets and journalist blogs and websites. During the course of the present study the researchers collected information about how integrated the media outlets that diffuse art and culture-related content and news are to the Semantic Web. The study uses quantitative metrics to evaluate a website’s adherence to Semantic Web standards and it proceeds to draw conclusions regarding how that integration affects their popularity in the modern competitive landscape of the Web. Full article
(This article belongs to the Special Issue Theory and Applications of Web 3.0 in the Media Sector)
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19 pages, 2662 KiB  
Article
A Semantic Preprocessing Framework for Breaking News Detection to Support Future Drone Journalism Services
by Michail Niarchos, Marina Eirini Stamatiadou, Charalampos Dimoulas, Andreas Veglis and Andreas Symeonidis
Future Internet 2022, 14(1), 26; https://doi.org/10.3390/fi14010026 - 10 Jan 2022
Cited by 4 | Viewed by 3195
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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18 pages, 1406 KiB  
Article
An AI-Enabled Framework for Real-Time Generation of News Articles Based on Big EO Data for Disaster Reporting
by Maria Tsourma, Alexandros Zamichos, Efthymios Efthymiadis, Anastasios Drosou and Dimitrios Tzovaras
Future Internet 2021, 13(6), 161; https://doi.org/10.3390/fi13060161 - 19 Jun 2021
Cited by 1 | Viewed by 2732
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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14 pages, 4369 KiB  
Article
From Rigidity to Exuberance: Evolution of News on Online Newspaper Homepages
by Simón Peña-Fernández, Miguel Ángel Casado-del-Río and Daniel García-González
Future Internet 2021, 13(6), 150; https://doi.org/10.3390/fi13060150 - 9 Jun 2021
Cited by 2 | Viewed by 3217
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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22 pages, 721 KiB  
Article
An AI-Enabled Stock Prediction Platform Combining News and Social Sensing with Financial Statements
by Traianos-Ioannis Theodorou, Alexandros Zamichos, Michalis Skoumperdis, Anna Kougioumtzidou, Kalliopi Tsolaki, Dimitris Papadopoulos, Thanasis Patsios, George Papanikolaou, Athanasios Konstantinidis, Anastasios Drosou and Dimitrios Tzovaras
Future Internet 2021, 13(6), 138; https://doi.org/10.3390/fi13060138 - 21 May 2021
Cited by 13 | Viewed by 4345
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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18 pages, 5942 KiB  
Article
A Web Interface for Analyzing Hate Speech
by Lazaros Vrysis, Nikolaos Vryzas, Rigas Kotsakis, Theodora Saridou, Maria Matsiola, Andreas Veglis, Carlos Arcila-Calderón and Charalampos Dimoulas
Future Internet 2021, 13(3), 80; https://doi.org/10.3390/fi13030080 - 22 Mar 2021
Cited by 28 | Viewed by 7158
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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