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The evolution of technology and the digital empowerment of society have led to the proliferation of Audiovisual Content Webs (ACWs) where users can share information and experiences, along with other commercial resources. ACWs have led to significant changes in the way users can select and access audiovisual content. The design of these websites combines various features, including a user community, streamed content, ticket sales, and recommendations, among others. Each ACW has a specific profile with respect to the mentioned variables. The aim of this study is to identify the critical success factors for a ACW, i.e., which features and the form they should take to attract followers, thus increasing the capacity to prescribe and broadcast content. Using qualitative comparative analysis (QCA), a formal analysis technique that allows the identification of combinations that produce a certain result, a sample of the 12 most representative cinema websites in Spain is analyzed. The results indicate that the incorporation of content recommendation systems and the connection with streaming platforms through which the content can be accessed are key factors in the success of these ACWs. This work contributes academically to the knowledge and explanation of audience behavior in the new audiovisual scenario. From a professional point of view, relevant design suggestions are offered to platform creators. Finally, the limitations of this work are described, and future lines of research are considered. [ABSTRACT FROM AUTHOR]

In the current techno-social environment the importance of providing personalized content for users of social platforms, continually adapting to their needs, is key to the success of the existing platforms. Recommender systems play a crucial role in this regard, but in many cases the level of customization provided is not enough. This article discusses two key aspects related to the development of recommender systems: proactivity and context-awareness. We propose a theoretical reference model for the creation of proactive recommender systems based on context-awareness information. In addition, we check its feasibility in two real-world scenarios where the model has been successfully implemented: banking and personal learning networks. Finally, future courses of action following the contributions proposed are highlighted, with special attention to potential applications in educational environments. [ABSTRACT FROM AUTHOR]

In a Web dominated by social media for information, relationships and communication, the established dynamics between content, people and technology change radically. Given the relevance of the user-generated content in such a scenario and its essentially relational nature, successfully locating the best sources of information requires the development of recommender systems that incorporate the social characteristic of scenarios built on a network that goes beyond the original Internet. The article provides a review of current approaches to the process of recommendation, placing them in the context of consolidated trends associated with the phenomenon of Social Computing, and highlights some lines of development in the area of redefining the problem of recommendation in a context dominated by social networks and user-generated content. [ABSTRACT FROM AUTHOR]

We present the theoretical and methodological foundations for the development of a multi-agent SDI service model for specialized digital libraries, applying semantic web technologies that permit more efficient information management, improving agent-user communication processes and facilitating accurate access to relevant resources. To do this, RSS feeds are used as "current awareness bulletins" to generate personalized bibliographic alerts. The SDI service model has an RSS feeds management module and an information push module. In the first module, resources are represented as RSS feed items and are also semi-automatically assigned subject terms by matching their associated keywords against the terms of a SKOS Core format thesaurus. In the information push module, bibliographic alerts are customized according to the preferences defined on users' profiles. [ABSTRACT FROM AUTHOR]