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In the digital era, social media has become a cornerstone for educational institutions, driving public engagement and enhancing institutional communication. This study utilizes AI-driven image processing and Web-enhanced Deep Learning (DL) techniques to investigate the effectiveness of King Faisal University's (KFU's) social media strategy as a case study, particularly on Twitter. By categorizing images into five primary event management categories and subcategories, this research provides a robust framework for assessing the social media content generated by KFU's administrative units. Seven advanced models were developed, including an innovative integration of Vision Transformers (ViTs) with Convolutional Neural Networks (CNNs), Long Short-Term Memory (LSTM) networks, VGG16, and ResNet. The AI-driven ViT-CNN hybrid model achieved perfect classification accuracy (100%), while the "Development and Partnerships" category demonstrated notable accuracy (98.8%), underscoring the model's unparalleled efficacy in strategic content classification. This study offers actionable insights for the optimization of AI-driven digital communication strategies and Web-enhanced data collection processes, aligning them with national development goals and Saudi Arabia's Vision 2030, thereby showcasing the transformative power of DL in event-centric management and the broader higher education landscape. [ABSTRACT FROM AUTHOR]

Social machines are a prominent focus of attention for those who work in the field of Web and Internet science. Although a number of online systems have been described as social machines (examples include the likes of Facebook, Twitter, Wikipedia, Reddit, and Galaxy Zoo), there is, as yet, little consensus as to the precise meaning of the term "social machine." This presents a problem for the scientific study of social machines, especially when it comes to the provision of a theoretical framework that directs, informs, and explicates the scientific and engineering activities of the social machine community. The present paper outlines an approach to understanding social machines that draws on recent work in the philosophy of science, especially work in so-called mechanical philosophy. This is what might be called a mechanistic view of social machines. According to this view, social machines are systems whose phenomena (i.e., events, states, and processes) are explained via an appeal to (online) socio-technical mechanisms. We show how this account is able to accommodate a number of existing attempts to define the social machine concept, thereby yielding an important opportunity for theoretical integration. [ABSTRACT FROM AUTHOR]

This paper examines the broad impact of digitalization on economic development. More specifically, it addresses the computer science-derived notion of "social machines", along with the invention of distributed ledger technologies (DLTs) (or blockchain), as potential signposts on the pathway to "smart(er) digital economies". The paper investigates blockchain-based ecosystems as examples of social machines that assist in economic "smartification" and development. It looks at distributed ledger-based communities (DLCs) that provide examples of functioning social machines for a variety of business and personal network communications purposes. It then analyses the scaleup of DLT-based social machines by comparison with "extension services", largely in education and agriculture, which are currently undergoing processes of digitalization. Overall, this conceptual study examines the general horizons and potential impact of blockchain and social machines on the provision of online products and services, across a range of sectors and industries. The paper offers interpretative assistance to managers, entrepreneurs, technology experts, and academics with lingering questions about blockchain in and for business and economic development. [ABSTRACT FROM AUTHOR]

Accessible and reusable datasets are a necessity to accomplish repeatable research. This requirement poses a problem particularly for web science, since scraped data comes in various formats and can change due to the dynamic character of the web. Further, usage of web data is typically restricted by copyright-protection or privacy regulations, which hinder publication of datasets. To alleviate these problems and reach what we define as "partial data repeatability", we present a process that consists of multiple components. Researchers need to distribute only a scraper and not the data itself to comply with legal limitations. If a dataset is re-scraped for repeatability after some time, the integrity of different versions can be checked based on fingerprints. Moreover, fingerprints are sufficient to identify what parts of the data have changed and how much. We evaluate an implementation of this process with a dataset of 250 million online comments collected from five different news discussion platforms. We re-scraped the dataset after pausing for one year and show that less than ten percent of the data has actually changed. These experiments demonstrate that providing a scraper and fingerprints enables recreating a dataset and supports the repeatability of web science experiments. [ABSTRACT FROM AUTHOR]

Akin to human transfer of experiences, transfer learning as a subfield of machine learning adapts knowledge acquired in one domain to a new domain. The authors systematically investigate how this concept might be applied to the study of users on emerging Web platforms, proposing a transfer learning–based approach, TraNet. [ABSTRACT FROM AUTHOR]

The authors make the case for creating a common architecture that interconnects otherwise disparate civic portals. They distinguish among core functions, complementary tools, and future features that could go into such a system, and consider its potential to create positive feedback loops that boost civic capacity and public legitimacy. [ABSTRACT FROM AUTHOR]

Globalization increasingly demands multilingual communication on the Internet, as well as in local communities. To create customized collaboration tools to support multilingual communities, the authors’ Language Grid, established ten years ago, has been improving Web-based services to communities throughout the world by providing highly adaptable infrastructure and access to a wide variety of language resources. [ABSTRACT FROM AUTHOR]

For marginalized communities around the globe, lack of stable Internet access can result in a “digital divide.” The author’s sociotechnical analysis of three marginalized communities—rural Native Americans in the US, Syrian refugees in Jordan, and Congolese refugees in Rwanda—identifies several key contributing factors, including aid agencies’ changing priorities, goals, and political concerns, as well as technological, geographic, and cultural challenges. Through novel insights about these contributing factors of digital divides, the author generates a set of technical, organizational, and policy solutions. [ABSTRACT FROM AUTHOR]

Although previous studies have investigated social media users’ privacy attitudes, little focus has been placed on understanding the degree of users’ concern about different types of private information or the changes in users’ privacy attitudes. This article presents novel insights on user attitudes toward 18 privacy items—identified through a review of the literature—and attitudinal changes through a comparative analysis. The authors also discuss the implications of the results that could better support users’ privacy management on social media. [ABSTRACT FROM AUTHOR]

The Web has transformed our lives, and a cursory review of recent headlines shows both our dreams and nightmares writ large as a result. Is it possible to retain the benefits through algorithms and apps for romance, books, music, and fitness, without suffering the devastation wrought by the hacking of health records, elections, and bank accounts? This special issue explores the many facets of Web Science, the study of the Web’s impact on our society and technology, and how we can use it to achieve our dreams without living our nightmares. [ABSTRACT FROM AUTHOR]

Jointly launched in mid-2011 by major search engines like Google and Bing, Schema.org is designed to facilitate structured and knowledge graph–centric search applications on the Web. The Web Data Commons project has crawled increasing amounts of Schema.org data in recent years, providing a golden opportunity for socio-technological data studies that consider the semantics of content. The authors present empirical studies of organizations in three economic sectors that expose semantically linked Schema.org annotations. [ABSTRACT FROM AUTHOR]

Scholars debate whether the arrival of articial super intelligence-a form of intelligence that signicantly exceeds the cognitive performance of humans in most domains- would bring positive or negative consequences. I argue that a third possibility is plausible yet generally overlooked: for several different reasons, an articial superintelligence might choose to exert no appreciable effect on the status quo ante (the already existing collective superintelligence of commercial cyberspace). Building on scattered insights from web science, philosophy, and cognitive psychology, I elaborate and defend this argument in the context of current debates about the future of articial intelligence. [ABSTRACT FROM PUBLISHER]

In Weaving the Web (2000), Berners-Lee defines Social Machines as biotechnologically hybrid Web-processes on the basis of which, 'high-level activities, which have occurred just within one human's brain, will occur among even larger more interconnected groups of people acting as if the shared a larger intuitive brain' (201-202). The analysis and design of Social Machines has already started attracting considerable attention both within the industry and academia. Web science, however, is still missing a clear definition of what a Social Machine is, which has in turn resulted in several calls for a 'philosophical engineering' (Halpin 2013; Hendler & Berners-Lee 2010); Halpin et al. 2010). This paper is a first attempt to respond to this call, by combining contemporary philosophy of mind and cognitive science with epistemology. The idea of philosophical engineering implies that a sufficiently good conception of Social Machines should be of both theoretical and practical advantage. To demonstrate how the present approach can satisfy both objectives it will be used in order to address one of Wikipedia's (the most famous Social Machine to date) most worrying concerns-i.e., the current and ongoing decline in the number of its active contributors (Halfacker et al. 2012). [ABSTRACT FROM AUTHOR]

Web science relies on an interdisciplinary approach that seeks to go beyond what any one subject can say about the World Wide Web. By incorporating numerous disciplinary perspectives and relying heavily on domain knowledge and expertise, data science has emerged as an important new area that integrates statistics with computational knowledge, data collection, cleaning and processing, analysis methods, and visualization to produce actionable insights from big data. As a discipline to use within Web science research, data science offers significant opportunities for uncovering trends in large Web-based datasets. A Web science observatory exemplifies this relationship by offering an online platform of tools for carrying out Web science research, allowing users to carry out data science techniques to produce insights into Web science issues such as community development, online behavior, and information propagation. The authors outline the similarities and differences of these two growing subject areas to demonstrate the important relationship developing between them. [ABSTRACT FROM PUBLISHER]

"Modernity" is a social, cultural or historical descriptor for a certain type of society or set of social arrangements. This monograph reviews narratives of digital modernity, without endorsing them; as narratives, they selectively discuss aspects of our sociotechnical context, descriptively, teleologically or normatively. Digital modernity narratives focus on the possibilities of the data gathered by an ambient data infrastructure, enabled by ubiquitous devices such as the smartphone, and activities such as social networking and e-commerce. Some emphasise continuities with 20th century modernity narratives, while others emphasise discontinuity, such as theories of the singularity. Digital modernity is characterised by: a subjunctive outlook where people's choices can be anticipated and improved upon; the valorisation of disruptive innovation on demand; and control provided by data analysis within a virtual realm (cyberspace or the metaverse) which can be extended and applied to the physical world (in such applications as the quantified self and the smart city). The synergies and tensions between these three aspects are explored, as are the opportunities for and dilemmas posed by misinformation. Five principles emerge from the study of relevant texts and business models: (1) the quantity of data being produced in the world has enabled, and been enabled by, technological, social, economic and cultural change, and as such is a marker of a qualitative change in modernity; (2) digital modernity is a subjunctive world in which reflexivity and choice are outsourced to the ambient data infrastructure; (3) since personalisation replaces choice in digital modernity, and since effective personalisation demands knowledge about the individual on the part of the personalised service provider, privacy is now an obstacle to the delivery of digital modernity; (4) to exist is to be backward; (5) the best that hapless reality can achieve is to get closer to the perfection of the algorithm and the data. To conclude, digital modernity is contrasted with other theories of the 21st century information society, including postmodernism, the network society and ANT. [ABSTRACT FROM AUTHOR]

2014 brought the 25th anniversary of the World Wide Web. There is general agreement that it represents one of the most influential software applications in history and has transformed many diverse elements of human interaction. The global impact of the Web would naturally lead to speculation about the future of the technology and attempts to understand what has, driven its evolution in the past and what will do so in the future. The definition of Web Science and its implementation in Web Observatories provide a viable mechanism for a more complete understanding of the technology and a paradigm for directing its future. Web Science also provides a powerful multi-disciplinary framework and compelling research opportunities. [ABSTRACT FROM AUTHOR]

Internet-based communication has transformed the way we stay in contact with family and friends who live remotely from us. Death puts such communication to an end and leaves us with just static data of our past interactions, such as pictures, chat protocols, video recordings, and letters. In this article, Martin Hepp describes how available computer technology could keep up the illusion of communicating with people beyond the barrier of death, and to continue to learn from them--how they lived, the places they've been to, the people they met, and how they would deal with our present challenges. In essence, such technology could reinforce and revitalize memories of a common past. [ABSTRACT FROM AUTHOR]

The aim of this article is to propose a methodological externalism that takes knowledge about science to be partly constituted by the environment. My starting point is the debate about extended cognition in contemporary philosophy and cognitive science. Externalists claim that human cognition extends beyond the brain and can be partly constituted by external devices. First, I show that most studies of public knowledge about science are based on an internalist framework that excludes the environment we usually utilize to make sense of science and does not allow the possibility of extended knowledge. In a second step, I argue that science communication studies should adopt a methodological externalism and accept that knowledge about science can be partly realized by external information resources such as Wikipedia. [ABSTRACT FROM PUBLISHER]

The emergence of Big Data is both promising and challenging for social research. This article suggests that realising this promise has been restricted by the methods applied in social science research, which undermine our potential to apprehend the qualities that make Big Data so appealing, not least in relation to the sociology of networks and flows. With specific reference to the micro-blogging website Twitter, the article outlines a set of methodological principles for approaching these data that stand in contrast to previous research; and introduces a new tool for harvesting and analysing Twitter built on these principles. We work our argument through an analysis of Twitter data linked to political protest over UK university fees. Our approach transcends earlier methodological limitations to offer original insights into the flow of information and the actors and networks that emerge in this flow. [ABSTRACT FROM AUTHOR]

Drawing mainly on the e-Diasporas Atlas project (www.e-diasporas.fr), this article seeks to understand how the web has affected diasporic self-representations. More specifically, by engaging with both media theory and migration studies, it addresses the new modes of boundary formations that arise in the context of migration flows, and how these are mediated by the web. It sheds light on two main levels of online diasporic identity-building. The first can be situated firmly within a paradigm of 'graphic reason', and relates to the socio-semiotic traces documented on diasporic websites. The second examines traces of another kind, which are formed by the hyperlinked networks of e-Diasporas on the web, and which can be situated within a paradigm of 'digital reason'. Some of the consequences for diasporic identity-formation are drawn out, particularly issues relating to strategies of visibility on the web. [ABSTRACT FROM AUTHOR]

Objectives: Detecting hints to public health threats as early as possible is crucial to prevent harm from the population. However, many disease surveillance strategies rely upon data whose collection requires explicit reporting (data transmitted from hospitals, laboratories or physicians). Collecting reports takes time so that the reaction time grows. Moreover, context information on individual cases is often lost in the collection process. This paper describes a system that tries to address these limitations by processing social media for identifying information on public health threats. The primary objective is to study the usefulness of the approach for supporting the monitoring of a population's health status. Methods: The developed system works in three main steps: Data from Twitter, blogs, and forums as well as from TV and radio channels are continuously collected and filtered by means of keyword lists. Sentences of relevant texts are classified relevant or irrelevant using a binary classifier based on support vector machines. By means of statistical methods known from biosurveillance, the relevant sentences are further analyzed and signals are generated automatically when unexpected behavior is detected. From the generated signals a subset is selected for presentation to a user by matching with user queries or profiles. In a set of evaluation experiments, public health experts assessed the generated signals with respect to correctness and relevancy. In particular, it was assessed how many relevant and irrelevant signals are generated during a specific time period. Results: The experiments show that the system provides information on health events identified in social media. Signals are mainly generated from Twitter messages posted by news agencies. Personal tweets, i.e. tweets from persons observing some symptoms, only play a minor role for signal generation given a limited volume of relevant messages. Relevant signals referring to real world outbreaks were generated by the system and monitored by epidemiologists for example during the European football championship. But, the number of relevant signals among generated signals is still very small: The different experiments yielded a proportion between 5 and 20% of signals regarded as "relevant" by the users. Vaccination or education campaigns communicated via Twitter as well as use of medical terms in other contexts than for outbreak reporting led to the generation of irrelevant signals. Conclusions: The aggregation of information into signals results in a reduction of monitoring effort compared to other existing systems. Against expectations, only few messages are of personal nature, reporting on personal symptoms. Instead, media reports are distributed over social media channels. Despite the high percentage of irrele vant signals generated by the system, the users reported that the effort in monitoring aggregated information in form of signals is less demanding than monitoring huge social-media data streams manually. It remains for the future to develop strategies for reducing false alarms. [ABSTRACT FROM AUTHOR]

The Web has enabled us to construct massive knowledge bases that enable both intelligent applications and complex analyses. The construction of these knowledge bases invariably involves combining multiple sources using a stack of human and automated decisions, which leads to an opaque process that hampers both transparency and repurposing. The intricacies of this problem are concretely formulated, along with potential research directions for addressing it. [ABSTRACT FROM AUTHOR]

An introduction is presented in which the editor discusses various reports within the issue on topics related to the role of social media, web semantics, online forums, and other technologies for web science on medicine and healthcare.

eParticipation involves the use of Information and Communication Technologies (ICTs) for facilitating the two-way communication between governments and citizens. Designing eParticipation activities is a complex task. Challenges include the need for interdisciplinary expertise and knowledge (e.g., in political, sociology, usability and technology domains) and the lack of widely accepted models and technological standards. This paper paves the way for the definition of a basic reference model for eParticipation, providing guidelines for the design, implementation and management of eParticipation web applications. This model was put into practice for the design of an eParticipation Framework helping users in designing, customizing and deploying web-based services for a given eParticipation process. The authors also report on the experimental use of the Framework in a group of Tuscany municipalities for carrying out participatory budget activities. [ABSTRACT FROM AUTHOR]

To understand and enable the evolution of the Web and to help address grand societal challenges, the Web must be observable at scale across space and time. That requires a globally distributed and collaborative Web Observatory. [ABSTRACT FROM PUBLISHER]

Modern Web sites use several techniques (e.g. DOM manipulation) that allow for the injection of new content into their Web pages (e.g. AJAX), as well as manipulation of the HTML DOM tree. This has the consequence that the Web pages that are presented to users (i.e. after browser processing) are different from the original structure and content that is transmitted through HTTP communication (i.e. after browser processing). This poses a series of challenges for Web accessibility evaluation, especially on automated evaluation software. This article details an experimental study designed to understand the differences posed by accessibility evaluation after Web browser processing. We implemented a Javascript-based evaluator, Qual Web, that can perform WCAG 2.0 based accessibility evaluations in the two phases of browser processing. Our study shows that, in fact, there are considerable differences between the HTML DOM trees in both phases, which have the consequence of having distinct evaluation results. We discuss the impact of these results in the light of the potential problems that these differences can pose to designers and developers that use accessibility evaluators that function before browser processing. [ABSTRACT FROM AUTHOR]

This article explores the notion of the Web-extended mind, which is the idea that the technological and informational elements of the Web can sometimes serve as part of the mechanistic substrate that realizes human mental states and processes. It is argued that while current forms of the Web may not be particularly suited to the realization of Web-extended minds, new forms of user interaction technology as well as new approaches to information representation do provide promising new opportunities for Web-based forms of cognitive extension. In addition, it is suggested that extended cognitive systems often rely on the emergence of social practices and conventions that shape how a technology is used. Web-extended minds may thus depend on forms of socio-technical co-evolution in which social forces and factors play just as important a role as do the processes of technology design and development. [ABSTRACT FROM AUTHOR]

The Web Science framework poses fundamental questions on the analysis of the Web, by focusing on how microscopic properties (e.g. at the level of a Web page or Web site) emerge into macroscopic properties and phenomena. One research topic on the analysis of the Web is Web accessibility evaluation, which centres on understanding how accessible a Web page is for people with disabilities. However, when framing Web accessibility evaluation on Web Science, we have found that existing research stays at the microscopic level. This article presents an experimental study on framing Web accessibility evaluation into Web Science's goals. This study resulted in novel accessibility properties of the Web not found at microscopic levels, as well as of Web accessibility evaluation processes themselves. We observed at large scale some of the empirical knowledge on how accessibility is perceived by designers and developers, such as the disparity of interpretations of accessibility evaluation tools warnings. We also found a direct relation between accessibility quality and Web page complexity. We provide a set of guidelines for designing Web pages, education on Web accessibility, as well as on the computational limits of large-scale Web accessibility evaluations. [ABSTRACT FROM AUTHOR]

This Special Issue of Sustainability devoted to the topic of "Big Data Research for Social Sciences and Social Impact" attracted significant attention of scholars, practitioners, and policy-makers from all over the world. Locating themselves at the cross-section of advanced information systems and computer science research and insights from social science and engineering, all papers included in this Special Issue contribute to the debate on the use of big data in social sciences and big data social impact. By promoting a debate on the multifaceted challenges that our societies are exposed to today, this Special Issue offers an in-depth, integrative, well-organized, comparative study into the most recent developments shaping the future directions of interdisciplinary research and policymaking. [ABSTRACT FROM AUTHOR]

This paper discusses issues that will affect the future development of the Web, either increasing its power and utility, or alternatively suppressing its development. It argues for the importance of the continued development of the Linked Data Web, and describes the use of linked open data as an important component of that. Second, the paper defends the Web as a read-write medium, and goes on to consider how the read-write Linked Data Web could be achieved. [ABSTRACT FROM AUTHOR]

What is the Web? What makes it work? And is it dying? This paper is drawn from a talk delivered by Prof. Zittrain to the Royal Society Discussion Meeting 'Web science: a new frontier' in September 2010. It covers key questions about the way the Web works, and how an understanding of its past can help those theorizing about the future. The original Web allowed users to display and send information from their individual computers, and organized the resources of the Internet with uniform resource locators. In the 20 years since then, the Web has evolved. These new challenges require a return to the spirit of the early Web, exploiting the power of the Web's users and its distributed nature to overcome the commercial and geopolitical forces at play. The future of the Web rests in projects that preserve its spirit, and in the Web science that helps make them possible. [ABSTRACT FROM AUTHOR]

IEEE Intelligent Systems pioneered AI, covering Web science and social computing. The magazine's current focus is predictive computing for predictive intelligence. Soon, reality and virtuality will be one, and the magazine should lead the effort in constructing intelligent systems for cyberspace, and move toward AI 3.0 with prescriptive computing for prescriptive intelligence. [ABSTRACT FROM AUTHOR]

The Web is a critical global infrastructure. Since its emergence in the mid-1990s, it has exploded into hundreds of billions of pages that touch almost all aspects of modern life. Today the jobs of more and more people depend on the Web. Media, banking, and healthcare are being revolutionized by it, and governments are even considering how to run their countries with it. This is the second half of a two-part special issue with some of the best articles from the inaugural Web Science Conference. The five articles in this issue, joined with the previous six, show the scope and scale of the many facets of the emerging science of the Web and illustrate some of the many ways the Web can be studied. [ABSTRACT FROM PUBLISHER]