Adaptation and personalization for web 2.0

6siAP-WEB 2.0, the International Workshop on Adaptation and Personalization for Web 2.0, held in Trento in connection to the first and seventeenth international conference on User Modeling, Adaptation and Personalization, UMAP 2009, aimed at discussing the challenges and approaches in adaptation and personalization for Web 2.0. Here we present an overview of the workshop. Thirteen full papers and five short papers were accepted, covering both theoretical and practical aspects of Personalization for Web 2.0. The papers discuss a wide range of areas including user awareness, recommender systems, user-generated content, and social networks.openopenDattolo, Antonina; Tasso, Carlo; Farzan, Rosta; Kleanthous, Styliani; Vallejo, David Bueno; Vassileva, JulitaDattolo, Antonina; Tasso, Carlo; Farzan, Rosta; Kleanthous, Styliani; Vallejo, David Bueno; Vassileva, Julit

Une méthode de detection et modélisation d'événements des messages sur Twitter

IRSTEA PUB00045753International audienceThis paper introduces TEWS —Twitter Events on the Semantic Web, pronounced like " news " —a semantic web tool for detection and representation of events taking as an input the social stream Twitter. The tool assists the user throughout a complete processing chain, starting from the detection of events on Twitter, their modeling and representation following the semantic web principles, to their storing in an RDF knowledge base that can be further published on the Web of Data

Improving Search Engine Results by Query Extension and Categorization

Since its emergence, the Internet has changed the way in which information is distributed and it has strongly influenced how people communicate. Nowadays, Web search engines are widely used to locate information on the Web, and online social networks have become pervasive platforms of communication. Retrieving relevant Web pages in response to a query is not an easy task for Web search engines due to the enormous corpus of data that the Web stores and the inherent ambiguity of search queries. We present two approaches to improve the effectiveness of Web search engines. The first approach allows us to retrieve more Web pages relevant to a user\u27s query by extending the query to include synonyms and other variations. The second, gives us the ability to retrieve Web pages that more precisely reflect the user\u27s intentions by filtering out those pages which are not related to the user-specified interests. Discovering communities in online social networks (OSNs) has attracted much attention in recent years. We introduce the concept of subject-driven communities and propose to discover such communities by modeling a community using a posting/commenting interaction graph which is relevant to a given subject of interest, and then applying link analysis on the interaction graph to locate the core members of a community

An Introduction to Social Semantic Web Mining & Big Data Analytics for Political Attitudes and Mentalities Research

The social web has become a major repository of social and behavioral data that is of exceptional interest to the social science and humanities research community. Computer science has only recently developed various technologies and techniques that allow for harvesting, organizing and analyzing such data and provide knowledge and insights into the structure and behavior or people on-line. Some of these techniques include social web mining, conceptual and social network analysis and modeling, tag clouds, topic maps, folksonomies, complex network visualizations, modeling of processes on networks, agent based models of social network emergence, speech recognition, computer vision, natural language processing, opinion mining and sentiment analysis, recommender systems, user profiling and semantic wikis. All of these techniques are briefly introduced, example studies are given and ideas as well as possible directions in the field of political attitudes and mentalities are given. In the end challenges for future studies are discussed

ABMS: Agent-based modeling and simulation in web service selection

Agent-based modeling and simulation (ABMS) is a new approach to modeling systems comprised of autonomous interacting agents. It promises to have an important role in research and education. Some researchers have contended that ABMS "is a third way of doing science". ABMS has been applied to a wide range of research in a varied number of complex domain problems. Social simulation is playing an increasingly important role in today's interconnected society. In this paper we apply agent based modeling and simulation to investigate the impact of Goldbaum's innovative "Follow the Leader" in social networks in web services selection using a recommender system that guides a user to select the best service that matches his requirements and preferences. We test and evaluate several customers' behaviors scenarios using our simulation tool "SSSS: Service Selection Simulation Studio". ©2009 IEEE

Hedonic Values And Utilitarian Values As Predicators Of Social Media Participation

This research proposes a model to investigate the behavior of posting articles and the continued use of social media via Babin’s value perspective. The antecedents of values are web quality and users’ emotions. The model was tested with PLS-Graph software based on its structural equation modeling approach. Data was gained from 310 users. The results revealed that antecedents have a strong impact on user values, which in turn influences users’ intention to post articles and continue to use social media. Several implications for research and practice have been derived from these findings