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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]

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.

The tourism and hospitality sectors have become increasingly important in the last few years and the companies operating in this field are constantly challenged with providing new innovative services. At the same time, (big-) data has become the “new oil” of this century and Knowledge Graphs are emerging as the most natural way to collect, refine, and structure this heterogeneous information. In this paper, we present a methodology for semi-automatic generating a Tourism Knowledge Graph (TKG), which can be used for supporting a variety of intelligent services in this space, and a new ontology for modelling this domain, the Tourism Analytics Ontology (TAO). Our approach processes and integrates data from Booking.com, Airbnb, DBpedia, and GeoNames. Due to its modular structure, it can be easily extended to include new data sources or to apply new enrichment and refinement functions. We report a comprehensive evaluation of the functional, logical, and structural dimensions of TKG and TAO.

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]

Abstract In this paper we explore the interrelationship between the sociotechnical-pedagogical culture of e-learning, the emerging disciplines of Web science, Social Sensing and that of Cognitive Computation–as an emerging paradigm of computation. We comment in particular on the importance of this relation for the development of learning-analytics discourse. Moreover, we present an initial relational framework between these disciplines and suggest how these relations can be exploited to solve problems in each area. This paper argues for (a) the particular importance of the abstract class of 'learning machines' for Web science, (b) understanding cognitive computation as a necessary practical framework for the increasingly dominating, situated informal learning context, and (c) the potential benefit of Web science frameworks for investigating both, contemporary research questions in e-learning and the development of theories for informal ubiquitous learning. Finally, we argue that exploring links between these disciplines is necessary for improving practical research, for the purpose of developing learning-analytics methodology for evaluating the growing types of modern e-learning contexts such as the informal situated learning context. Highlights • Web Science, Cognitive Computing, E-learning and Social Sensing are connected. • Informal situated-learning is becoming the most prevalent form of e-learning. • Situated learning argued to be significant form of social machine (from Web Science). • Progress in learning-analytics depends on exploiting relations with these disciplines. [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]

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]

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]

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]

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]

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]

The study of social phenomena is becoming increasingly reliant on big data from online social networks. Broad access to social media data, however, requires software development skills that not all researchers possess. Here we present the IUNI Observatory on Social Media, an open analytics platform designed to facilitate computational social science. The system leverages a historical, ongoing collection of over 70 billion public messages from Twitter. We illustrate a number of interactive open-source tools to retrieve, visualize, and analyze derived data from this collection. The Observatory, now available at osome.iuni.iu.edu, is the result of a large, six-year collaborative effort coordinated by the Indiana University Network Science Institute.

Discourse in the field of “cyber culture” largely does not take into account the major shift in constituent technology that has begun to advance the Web from one based solely on human-understandable hypertext documents to one based on machine-understandable data. Such innovation includes the refinement of new search engine technology to mine data in Web services applications (the “Deep Web”) coupled with the desire to annotate data with mark-up languages that facilitate greater interactivity and infer meaning within either user-created knowledge representation models (“folksonomies” as a part of “Web 2.0”) or more rigid ontological structures (part of the “Semantic Web” or “Web 3.0”). In this paper, I consider this overall evident and predicted shift from a “Web of documents” to a “Web of data” to be the central element in the creation of the next-generation of the Web, and the recent drive to study it within an integrated framework known as “Web Science”. Central to this shift is the need to reconsider not only the cultural aspects of the medium, but also the interactions between cultural theory and technical texts. I conclude that with the emergence of certain new technology the entire concept of intellectual property, and more specifically where value ultimately lies in terms of the creation of cultural product, is also changing. Within, I thus focus on alternative frameworks (namely the work of Yochai Benkler) to conceptualize knowledge production, in order to re-examine issues of Web-enabled participatory culture. In order to highlight new cultural paradigms, opportunities and challenges, I discuss how the concept of “social production” may foster a “cultural democracy” that transcends traditional hegemonic conditions that encumber publics.

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]