The state-of-the-art in personalized recommender systems for social networking

With the explosion of Web 2.0 application such as blogs, social and professional networks, and various other types of social media, the rich online information and various new sources of knowledge flood users and hence pose a great challenge in terms of information overload. It is critical to use intelligent agent software systems to assist users in finding the right information from an abundance of Web data. Recommender systems can help users deal with information overload problem efficiently by suggesting items (e.g., information and products) that match users’ personal interests. The recommender technology has been successfully employed in many applications such as recommending films, music, books, etc. The purpose of this report is to give an overview of existing technologies for building personalized recommender systems in social networking environment, to propose a research direction for addressing user profiling and cold start problems by exploiting user-generated content newly available in Web 2.0

Tagging, Folksonomy & Co - Renaissance of Manual Indexing?

This paper gives an overview of current trends in manual indexing on the Web. Along with a general rise of user generated content there are more and more tagging systems that allow users to annotate digital resources with tags (keywords) and share their annotations with other users. Tagging is frequently seen in contrast to traditional knowledge organization systems or as something completely new. This paper shows that tagging should better be seen as a popular form of manual indexing on the Web. Difference between controlled and free indexing blurs with sufficient feedback mechanisms. A revised typology of tagging systems is presented that includes different user roles and knowledge organization systems with hierarchical relationships and vocabulary control. A detailed bibliography of current research in collaborative tagging is included.Comment: Preprint. 12 pages, 1 figure, 54 reference

Tag-Aware Recommender Systems: A State-of-the-art Survey

In the past decade, Social Tagging Systems have attracted increasing attention from both physical and computer science communities. Besides the underlying structure and dynamics of tagging systems, many efforts have been addressed to unify tagging information to reveal user behaviors and preferences, extract the latent semantic relations among items, make recommendations, and so on. Specifically, this article summarizes recent progress about tag-aware recommender systems, emphasizing on the contributions from three mainstream perspectives and approaches: network-based methods, tensor-based methods, and the topic-based methods. Finally, we outline some other tag-related works and future challenges of tag-aware recommendation algorithms.Comment: 19 pages, 3 figure

Competences for collaboration and knowledge sharing in digital society - a case study with an erasmus intensive programme

With the advent of social and collaborative environments, students became more active and participative - they not only have access to contents but also create and share them, becoming proactive. Communication has evolved, and with this evolution came the new media and the possibility of live conferencing, video sharing, social networking, collaborative tools, allowing the student to create, work collaboratively and communicate in a more direct way with their peers and their teachers. Instead of merely searching for information, applications such as bookmarking, feeds, tweeter and pinboards, digital portfolios, etc., along with the possibility of creating your own personal webpage, today’s Web gives students also the chance to create a PLE - A Personal Learning Environment. A PLE “recognizes that learning is continuing and seeks to provide tools to support that learning” (Attwell, 2007). The Individuals are responsible for the management of their own learning environment and for the selection of tools and contexts where learning will take place. Students need to acquire certain skills and competences, specific of a digital and connected society, in order to “effectively benefit from e-government, e-learning and e-health services, and participate actively in the knowledge society as co-creators, and not simply consumers, as highlighted by the European e-skills strategy” (McCormack, 2010). To only possess hard skills (that comes with experience and formal education) may not be enough to get someone a job. Besides e-skills and e-literacy competences, soft and social skills are also required. These can be practiced and enhanced in virtual environments. Digital literacy, and therefore e-skills, are transversal competences needed to every citizen. In this paper we will present the results of a case study carried out with attendees of an Erasmus Intensive Programme, which has promoted the development of digital literacies among participants. The Programme took place during 2013 summer and involved students and teachers (of teacher education and social service fields) from 3 different countries. The classes covered different tools and 12 tutors were involved. The main objectives were to provide students with information and communication technologies (ICT) skills for a digital society, namely: • Identification of students’ competencies in ICT; • Present students with different available collaboration tools by exploring the web 2.0; • Selection of specific tools to create students' personal learning environment (PLE); • Acquire necessary knowledge to master the selected tools; • Work collaboratively with the web 2.0 tools; • Establish methods for instruction and course design based on Web 2.0 (teacher education) with the goal to integrate technology enhanced learning and individual knowledge management in educational processes. At the end attendees were able to: • Master the different tools & services; • Be capable to use and select the most adequate web 2.0 tools & services; • Create and manage their PLE; • Share and to work collaboratively; • Be digitally skilled.info:eu-repo/semantics/publishedVersio

Exploring the Structure of Library and Information Science Web Space Based on Multivariate Analysis of Social Tags

Introduction. This study examines the structure of Web space in the field of library and information science using multivariate analysis of social tags from the Website, Delicious.com. A few studies have examined mathematical modelling of tags, mainly examining tagging in terms of tri-partite graphs, pattern tracing and descriptive statistics. This study is one of the few studies to employ multivariate analysis in investigating dimensions of Web spaces based on social tagging data. Method. This study examines the post data collected from a set of library and information science related Websites bookmarked on Delicious.com using a Web crawler. Post data consist of the URL, usernames, tags and comments assigned by users of Delicious.com. The collected tag data were analysed based on multivariate methods, such as multidimensional scaling and structural equation modelling. Analysis. Collected data were first analysed using multidimensional scaling to explore initial relationships amongst the selected Websites. Then, confirmatory factor analysis based on structural equation modelling was employed to examine the hierarchical structure of the library & information science Web space. Results. Social tag data exhibit different dimensions in the Web space of the library and information science field. In addition, social tags confirmed the hierarchical structure of the field by showing significantly stronger relationships between the sites with similar characteristics. That is, the structure of the tagging data shows similar connections to those present in the real world. Conclusions. This study suggests a new statistical approach in social tagging and Web space analysis studies. Tag information can be used to explain the hierarchical structure of a certain domain. Methodologically, this study suggests that structural equation modelling can be a compelling method to explore hierarchal structures of nodes on the Web space

Linking information and people in a social system for academic conferences

This paper investigates the feasibility of maintaining a social information system to support attendees at an academic conference. The main challenge of this work was to create an infrastructure where users’ social activities, such as bookmarking, tagging, and social linking could be used to enhance user navigation and maximize the users’ ability to locate two important types of information in conference settings: presentations to attend and attendees to meet. We developed Conference Navigator 3, a social conference support system that integrates a conference schedule planner with a social linking service. We examined its potential and functions in the context of a medium-scale academic conference. In this paper, we present the design of the system’s socially enabled features and report the results of a conference-based study. Our study demonstrates the feasibility of social information systems for supporting academic conferences. Despite the low number of potential users and the short timeframe in which conferences took place, the usage of the system was high enough to provide sufficient data for social mechanisms. The study shows that most critical social features were highly appreciated and used, and provides direction for further research

Link creation and profile alignment in the aNobii social network

The present work investigates the structural and dynamical properties of aNobii\footnote{http://www.anobii.com/}, a social bookmarking system designed for readers and book lovers. Users of aNobii provide information about their library, reading interests and geographical location, and they can establish typed social links to other users. Here, we perform an in-depth analysis of the system's social network and its interplay with users' profiles. We describe the relation of geographic and interest-based factors to social linking. Furthermore, we perform a longitudinal analysis to investigate the interplay of profile similarity and link creation in the social network, with a focus on triangle closure. We report a reciprocal causal connection: profile similarity of users drives the subsequent closure in the social network and, reciprocally, closure in the social network induces subsequent profile alignment. Access to the dynamics of the social network also allows us to measure quantitative indicators of preferential linking.Comment: http://www.iisocialcom.org/conference/socialcom2010

Identifying Social Computing Dimensions: A Multidimensional Scaling Study

Despite an increasing popularity, the impact and benefits of corporate social computing remain unclear. This paper aims at rigorously studying social computing tools as a new class of technology and provides a holistic definition and characterization. After a comprehensive literature review, we empirically explored the defining attributes and underlying dimensions of social computing as a whole using the multidimensional scaling (MDS) methodology. The study found that 13 representative exemplar tools differ over three dimensions: (i) their ability to support social interactions, social relations, and communities, (ii) their hedonic versus utilitarian focus, and (iii) their ability to support convergence versus conveyance of generated content. A Property Fitting (ProFit) study confirmed the interpretation of the dimensions. This provided a better understanding of this technology and allowed us to better theorize about the expected benefits and impacts of social computing on organizations, to offer guidelines for adoption and provide suggestions for future research