Spam-Bekämpfung im Web 2.0 — auch eine Frage des Datenschutzes

Auch Web 2.0-Anwendungen sind von Spam in Form von ungewollten, oft kommer ziell motivierten Eintr?gen betroffen, die den erwünschten Nutzern den Spa? und dem Anbieter Speicherkapazit?ten rauben. Im Praxisbeispiel werden anhand des Social Bookmarking-Dienstes BibSonomy typische Spam-Erkennungsverfahren und -Merkmale vorgestellt, auf ihre datenschutzrechtliche Zul?ssigkeit sowie ihre Treffsicherheit geprüft und mit Anregungen zur datenschutzfreundlichen Merkmalsauswahl erg?nzt.     

Social networks on the Internet

The rapid development and expansion of the Internet and the social–based services comprised by the common Web 2.0 idea provokes the creation of the new area of research interests, i.e. social networks on the Internet called also virtual or online communities. Social networks can be either maintained and presented by social networking sites like MySpace, LinkedIn or indirectly extracted from the data about user interaction, activities or achievements such as emails, chats, blogs, homepages connected by hyperlinks, commented photos in multimedia sharing system, etc. A social network is the set of human beings or rather their digital representations that refer to the registered users who are linked by relationships extracted from the data about their activities, common communication or direct links gathered in the internet–based systems. Both digital representations named in the paper internet identities as well as their relationships can be characterized in many different ways. Such diversity yields for building a comprehensive and coherent view onto the concept of internet–based social networks. This survey provides in–depth analysis and classification of social networks existing on the Internet together with studies on selected examples of different virtual communities.     

Adaptive systems in the era of the semantic and social web, a survey

In this paper we provide a classification of adaptive systems with respect to the kind of semantic technology they exploit to accomplish or improve specific adaptation and user modeling tasks. This classification is based on a distinction between strong semantic techniques and weak semantic techniques. The former are techniques based on the Semantic Web, while the latter regard technologies that, in different ways, annotate resources, enriching their meaning. This second category includes, in particular, Web 2.0 social annotations and mixed approaches between social annotations and Semantic Web techniques. While the impact of the Semantic Web on adaptive systems has been discussed in several survey papers, the potential of weak semantic technologies has, so far, received little attention. The aim of this analysis is to fill this gap. Therefore, we will discuss contributions and limits of both approaches, but we will focus special attention on weak semantic adaptive systems.     

Cross-system user modeling and personalization on the Social Web

In order to adapt functionality to their individual users, systems need information about these users. The Social Web provides opportunities to gather user data from outside the system itself. Aggregated user data may be useful to address cold-start problems as well as sparse user profiles, but this depends on the nature of individual user profiles distributed on the Social Web. For example, does it make sense to re-use Flickr profiles to recommend bookmarks in Delicious? In this article, we study distributed form-based and tag-based user profiles, based on a large dataset aggregated from the Social Web. We analyze the completeness, consistency and replication of form-based profiles, which users explicitly create by filling out forms at Social Web systems such as Twitter, Facebook and LinkedIn. We also investigate tag-based profiles, which result from social tagging activities in systems such as Flickr, Delicious and StumbleUpon: to what extent do tag-based profiles overlap between different systems, what are the benefits of aggregating tag-based profiles. Based on these insights, we developed and evaluated the performance of several cross-system user modeling strategies in the context of recommender systems. The evaluation results show that the proposed methods solve the cold-start problem and improve recommendation quality significantly, even beyond the cold-start.     

Integrating organizational,social, and individual perspectives in Web 2.0-based workplace e-learning

E-learning is emerging as a popular approach of education in the workplace by virtue of its flexibility to access, just-in-time delivery, and cost-effectiveness. To improve social interaction and knowledge sharing in e-learning, Web 2.0 is increasingly utilized and integrated with e-learning applications. However, existing social learning systems fail to align learning with organizational goals and individual needs in a systemic way. The dominance of technology-oriented approaches makes e-learning applications less goal-effective and poor in quality and design. To solve the problem, we address the requirement of integrating organizational, social, and individual perspectives in the development of Web 2.0 e-learning systems. To fulfill the requirement, a key performance indicator (KPI)-oriented approach is presented in this study. By integrating a KPI model with Web 2.0 technologies, our approach is able to: 1) set up organizational goals and link the goals with expertise required for individuals; 2) build a knowledge network by linking learning resources to a set of competences to be developed and a group of people who learn and contribute to the knowledge network through knowledge creation, sharing, and peer evaluation; and 3) improve social networking and knowledge sharing by identifying each individual’s work context, expertise, learning need, performance, and contribution. The mechanism of the approach is explored and elaborated with conceptual frameworks and implementation technologies. A prototype system for Web 2.0 e-learning has been developed to demonstrate the effectiveness of the approach.     

Fuzzy ontologies-based user profiles applied to enhance e-learning activities

Nowadays, the impact of technological developments on improving human activities is becoming more evident. In e-learning, this situation is no different. There are common to use systems that assist the daily activities of students and teachers. Typically, e-learning recommender systems are focused on students; however, teachers can also benefit from these type of tools. A recommender system can propose actions and resources that facilitate teaching activities like structuring learning strategies. In any case, a complete user’s representation is required. This paper shows how a fuzzy ontology can be used to represent user profiles into a recommender engine and enhances the user’s activities into e-learning environments. A fuzzy ontology is an extension of domain ontologies for solving the problems of uncertainty in sharing and reusing knowledge on the Semantic Web. The user profile is built from learning objects published by the user himself into a learning object repository. The initial experiment confirms that the automatically obtained fuzzy ontology is a good representation of the user’s preferences. The experiment results also indicate that the presented approach is useful and warrants further research in recommending and retrieval information.     

Using the Semantic Web for linking and reusing data across Web 2.0 communities

Large volumes of content (bookmarks, reviews, videos, etc.) are currently being created on the “Social Web”, i.e. on Web 2.0 community sites, and this content is being annotated and commented upon. The ability to view an individual's entire contribution to the Social Web would be an interesting and valuable service, particularly important as social networks are often being formed through created content and things that people have in common (“object-centred sociality”). SIOC is a Semantic Web research project that aims to describe online communities on the Social Web. This paper describes how SIOC and the Semantic Web can enable linking and reuse scenarios of data from Web 2.0 community sites, and introduces a SIOC Types module to further specify the type of content items and act as a “glue” between user posts and the content items created and annotated by users.     

Web 2.0 Recommendation service by multi-collaborative filtering trust network algorithm

Recommendation Services (RS) are an essential part of online marketing campaigns. They make it possible to automatically suggest advertisements and promotions that fit the interests of individual users. Social networking websites, and the Web 2.0 in general, offer a collaborative online platform where users socialize, interact and discuss topics of interest with each other. These websites have created an abundance of information about users and their interests. The computational challenge however is to analyze and filter this information in order to generate useful recommendations for each user. Collaborative Filtering (CF) is a recommendation service technique that collects information from a user’s preferences and from trusted peer users in order to infer a new targeted suggestion. CF and its variants have been studied extensively in the literature on online recommending, marketing and advertising systems. However, most of the work done was based on Web 1.0, where all the information necessary for the computations is assumed to always be completely available. By contrast, in the distributed environment of Web 2.0, such as in current social networks, the required information may be either incomplete or scattered over different sources. In this paper, we propose the Multi-Collaborative Filtering Trust Network algorithm, an improved version of the CF algorithm designed to work on the Web 2.0 platform. Our simulation experiments show that the new algorithm yields a clear improvement in prediction accuracy compared to the original CF algorithm.     

How should I explain? A comparison of different explanation types for recommender systems

Recommender systems help users locate possible items of interest more quickly by filtering and ranking them in a personalized way. Some of these systems provide the end user not only with such a personalized item list but also with an explanation which describes why a specific item is recommended and why the system supposes that the user will like it. Besides helping the user understand the output and rationale of the system, the provision of such explanations can also improve the general acceptance, perceived quality, or effectiveness of the system.In recent years, the question of how to automatically generate and present system-side explanations has attracted increased interest in research. Today some basic explanation facilities are already incorporated in e-commerce Web sites such as Amazon.com. In this work, we continue this line of recent research and address the question of how explanations can be communicated to the user in a more effective way.In particular, we present the results of a user study in which users of a recommender system were provided with different types of explanation. We experimented with 10 different explanation types and measured their effects in different dimensions. The explanation types used in the study include both known visualizations from the literature as well as two novel interfaces based on tag clouds. Our study reveals that the content-based tag cloud explanations are particularly helpful to increase the user-perceived level of transparency and to increase user satisfaction even though they demand higher cognitive effort from the user. Based on these insights and observations, we derive a set of possible guidelines for designing or selecting suitable explanations for recommender systems.     

Towards building a blog preservation platform

Social media content and user participation has increased dramatically since the advent of Web 2.0. Blogs have become relevant to every aspect of business and personal life. Nevertheless, we do not have the right tools to aggregate and preserve blog content correctly, as well as to manage blog archives effectively. Given the rising importance of blogs, it is crucial to build systems to facilitate blog preservation, safeguarding an essential part of our heritage that will prove valuable for current and future generations. In this paper, we present our work in progress towards building a novel blog preservation platform featuring robust digital preservation, management and dissemination facilities for blogs. This work is part of the BlogForever project which is aiming to make an impact to the theory and practice of blog preservation by creating guidelines and software that any individual or organization could use to preserve their blogs.     

Building a knowledge portal for communities based on personalized functionalities

Over the last decade portals have become an important facet of the Web and of structured communities like companies. This paper presents a knowledge portal that has been developed to provide an improved support to the users during their navigation and access to information. The idea of this work is to create a smooth and richer connection between the users and the relevant data. These tasks have been done by considering personalization aspects (i.e., user preferences and user activities), based on ontological user profiles aimed at managing information effectively. The portal has been tested within the Knowledge-Based Management System 2.0 Project.     

融合社会关系的社交网络情感分析综述

随着以用户为中心的Web 2.0的发展,社交网络平台以惊人的影响力渗入到生活的方方面面,对社交网络中的内容进行情感分析已经成为热点研究课题.Twitter、新浪微博等在线社交网站吸引了大量用户,通过用户间的交互,产生了许多包含用户间社会关系的信息,并且这些社会关系被广泛应用于社交网络的情感分析.融合社会关系的社交网络情...     

Broadcasting and personalization of user-generated contents in DVB-H mobile networks

During the last years, we have witnessed the boom of the digital market due to the proliferation of emergent audiovisual services and the increasing number of broadband networks. In this scenario, users insistently demand innovative services for exchanging and sharing their own audiovisual contents. In order to meet these needs, in this paper, we propose a system that broadcasts user-generated audiovisual contents for handheld devices in a mobile network based on the DVB-H broadcasting standard. Besides, our system offers diverse value-added services to these new active users, such as: (1) annotation, sharing and personalized distribution of audiovisual contents, (2) multi modal access, via Web or by client applications running locally in the handheld device, and (3) exploitation of return channels to transmit interactive contents that enhance the user’s experience. To achieve these goals, our system adopts well-known technologies for broadcasting and semantic annotation of audiovisual contents, as well as emergent technology from Web 2.0 and Semantic Web. We have carried out tests involving a group of students from the University of Vigo, who were satisfied with the personalization capabilities offered by our TV system for mobile settings.     

A Unified Framework for Providing Recommendations in Social Tagging Systems Based on Ternary Semantic Analysis

Social Tagging is the process by which many users add metadata in the form of keywords, to annotate and categorize items (songs, pictures, Web links, products, etc.). Social tagging systems (STSs) can provide three different types of recommendations: They can recommend 1) tags to users, based on what tags other users have used for the same items, 2) items to users, based on tags they have in common with other similar users, and 3) users with common social interest, based on common tags on similar items. However, users may have different interests for an item, and items may have multiple facets. In contrast to the current recommendation algorithms, our approach develops a unified framework to model the three types of entities that exist in a social tagging system: users, items, and tags. These data are modeled by a 3-order tensor, on which multiway latent semantic analysis and dimensionality reduction is performed using both the Higher Order Singular Value Decomposition (HOSVD) method and the Kernel-SVD smoothing technique. We perform experimental comparison of the proposed method against state-of-the-art recommendation algorithms with two real data sets (Last.fm and BibSonomy). Our results show significant improvements in terms of effectiveness measured through recall/precision.     

The two cultures: Mashing up Web 2.0 and the Semantic Web

A common perception is that there are two competing visions for the future evolution of the Web: the Semantic Web and Web 2.0. A closer look, though, reveals that the core technologies and concerns of these two approaches are complementary and that each field can and must draw from the other’s strengths. We believe that future Web applications will retain the Web 2.0 focus on community and usability, while drawing on Semantic Web infrastructure to facilitate mashup-like information sharing. However, there are several open issues that must be addressed before such applications can become commonplace. In this paper, we outline a semantic weblogs scenario that illustrates the potential for combining Web 2.0 and Semantic Web technologies, while highlighting the unresolved issues that impede its realization. Nevertheless, we believe that the scenario can be realized in the short-term. We point to recent progress made in resolving each of the issues as well as future research directions for each of the communities.     

Inclusive social tagging and its support in Web 2.0 services

This paper investigates the Web 2.0 phenomenon of social tagging in the context of existing approaches to semantic data structuring. Social tagging is embedded into the space spanned by current structuring approaches like taxonomies, meta-data, and ontologies in order to identify its semantic and pragmatic foundations. Thereby, we use the Inclusive Universal Access paradigm to assess social tagging with respect to socio-technical criteria for inclusive and barrier-free provision and usage of web services. As a result of this analysis we propose a concept we chose to call “Inclusive Social Tagging”. We subsequently use the requirements set forth by this concept to assess the tagging functionality of currently popular Web 2.0 services. We found that these services differ significantly in their implementation of tagging functionality, and we did not discover any service providing full compliance with Inclusive Social Tagging requirements.     

SweetWiki: A semantic wiki

Everyone agrees that user interactions and social networks are among the cornerstones of “Web 2.0”. Web 2.0 applications generally run in a web browser, propose dynamic content with rich user interfaces, offer means to easily add or edit content of the web site they belong to and present social network aspects. Well-known applications that have helped spread Web 2.0 are blogs, wikis, and image/video sharing sites; they have dramatically increased sharing and participation among web users. It is possible to build knowledge using tools that can help analyze users’ behavior behind the scenes: what they do, what they know, what they want. Tools that help share this knowledge across a network, and that can reason on that knowledge, will lead to users who can better use the knowledge available, i.e., to smarter users. Wikipedia, a wildly successful example of web technology, has helped knowledge-sharing between people by letting individuals freely create and modify its content. But Wikipedia is designed for people—today's software cannot understand and reason on Wikipedia's content. In parallel, the “semantic web”, a set of technologies that help knowledge-sharing across the web between different applications, is starting to gain attraction. Researchers have only recently started working on the concept of a “semantic wiki”, mixing the advantages of the wiki and the technologies of the semantic web. In this paper we will present a state-of-the-art of semantic wikis, and we will introduce SweetWiki, an example of an application reconciling two trends of the future web: a semantically augmented web and a web of social applications where every user is an active provider as well as a consumer of information. SweetWiki makes heavy use of semantic web concepts and languages, and demonstrates how the use of such paradigms can improve navigation, search, and usability.     

Deploying and managing Web services: issues, solutions, and directions

Web services are expected to be the key technology in enabling the next installment of the Web in the form of the Service Web. In this paradigm shift, Web services would be treated as first-class objects that can be manipulated much like data is now manipulated using a database management system. Hitherto, Web services have largely been driven by standards. However, there is a strong impetus for defining a solid and integrated foundation that would facilitate the kind of innovations witnessed in other fields, such as databases. This survey focuses on investigating the different research problems, solutions, and directions to deploying Web services that are managed by an integrated Web Service Management System (WSMS). The survey identifies the key features of a WSMS and conducts a comparative study on how current research approaches and projects fit in. This research is supported by the National Institutes of Health’s NLM grant 1-R03-LM008140-01.     

Modeling use of enterprise resource planning systems: a path analytic study

In this research, we evaluated user participation and involvement in the context of enterprise resource planning (ERP) systems. Since ERP systems are enterprise-wide in scope, these systems have a high level of complexity, and require a different implementation methodology. While most studies analyze implementation at an organization or industry level, there is a dearth in research in ERP system adoption at the individual or user level. In our study, we examine ERP system acceptance at the individual level. In this research, we expected to find differences in the nature of user participation and involvement in ERP compared to other information systems. Using Barki and Hartwick's extension of the theory of reasoned action, a revised model was developed and tested empirically. While Barki and Hartwick's model explains user behavior vis-à-vis user participation and involvement, a more parsimonious model demonstrates that usage dynamics in ERP implementation are different. We complemented our statistical analysis by three case studies. Based on our results we believe that, given the nature of ERP and its implementation, traditionally formalized links between influencers of users' attitude and involvement may need to be revised. We have discussed why we need to seek alternate forms of influencers. In doing so, we suggest that investments be made in preparatory work practices and employee development prior to ERP decisions. Such investments are complementary to information technology and are widespread throughout the firm. We believe that such investments will play a significant role in influencing the attitude of users toward any system and also their involvement.     

Estimating user interaction strength in distributed online networks

User interactions are indispensable for any online network to thrive, especially for BitTorrent‐like and Web real‐time communication‐based distributed online networks that rely on users' collective contributions instead of the help of central servers. User interactions provide fine‐grained information for many applications, such as security enhancement and cooperation promotion. To date, several schemes for estimating user interaction strength in centralized online networks have been proposed. In contrast, we present design, deployment, and analysis of UISE for user interaction strength estimation in distributed online networks. Among the strong points of UISE is that it captures both direct and indirect user interactions, and that it scales with only partial information dissemination. We apply UISE to devise the first distributed scheme for online time estimation and we implement it into Tribler, a distributed online network for media and social applications like file sharing, streaming, and voting. We demonstrate the accuracy and the scalability of UISE with different information dissemination protocols and user behaviors using simulations, emulations, and a real‐world deployment. Copyright © 2015 John Wiley & Sons, Ltd.