Sociological ontology of the digital public sphere : the case of Web 2.0/3.0

Digital public sphere is immersed in the present conjuncture of accelerated transformation and probable rupture, which certainly will affect the way we exercise our citizenship in contemporary times. This social and political tsunami is partly based on the change of paradigm of Web 2.0 or Social Web to Web 3.0 or Semantic Web. To clarify such a process, this paper discusses some of the key issues and theoretical positions on public space, from seminal Habermas’s perspective to new problematics raised by the networked society. The author suggests the construction of a Sociological Ontology of Social and Semantic Web, based on a Semantic-Logical Sociology and Methodology. These procedures are applied through the analysis and hermeneutics of a Wikipedia page entitled ‘Web 2.0’, where sociological experimental tools are used, as Semantic-Logical fields, trees and networks, central and peripheral concepts, and trichotomies

Sociological ontology of the digital public sphere: the case of Web 2.0/3.0

Digital public sphere is immersed in the present conjuncture of accelerated transformation and probable rupture, which certainly will affect the way we exercise our citizenship in contemporary times. This social and political tsunami is partly based on the change of paradigm of Web 2.0 or Social Web to Web 3.0 or Semantic Web. To clarify such a process, this paper discusses some of the key issues and theoretical positions on public space, from seminal Habermas’s perspective to new problematics raised by the networked society. The author suggests the construction of a Sociological Ontology of Social and Semantic Web, based on a Semantic-Logical Sociology and Methodology. These procedures are applied through the analysis and hermeneutics of a Wikipedia page entitled ‘Web 2.0’, where sociological experimental tools are used, as Semantic-Logical fields, trees and networks, central and peripheral concepts, and trichotomies

Towards OpenMath Content Dictionaries as Linked Data

"The term 'Linked Data' refers to a set of best practices for publishing and connecting structured data on the web". Linked Data make the Semantic Web work practically, which means that information can be retrieved without complicated lookup mechanisms, that a lightweight semantics enables scalable reasoning, and that the decentral nature of the Web is respected. OpenMath Content Dictionaries (CDs) have the same characteristics - in principle, but not yet in practice. The Linking Open Data movement has made a considerable practical impact: Governments, broadcasting stations, scientific publishers, and many more actors are already contributing to the "Web of Data". Queries can be answered in a distributed way, and services aggregating data from different sources are replacing hard-coded mashups. However, these services are currently entirely lacking mathematical functionality. I will discuss real-world scenarios, where today's RDF-based Linked Data do not quite get their job done, but where an integration of OpenMath would help - were it not for certain conceptual and practical restrictions. I will point out conceptual shortcomings in the OpenMath 2 specification and common bad practices in publishing CDs and then propose concrete steps to overcome them and to contribute OpenMath CDs to the Web of Data.Comment: Presented at the OpenMath Workshop 2010, http://cicm2010.cnam.fr/om

Compounding the Results: The Integration of Virtual Worlds With the Semantic Web

Over the past 20 years, governmental use of Web-base information and technologies has continually expanded taking advantage of the Web's vast, ever- expanding volumes of browser-accessible information. Now, it infuses two new technologies, the first one espousing a world where semantic-powered applications become knowledgeable assistants for Web users. The second new technology takes a perceivably flat two-dimensional approach to presenting current Web-content and adds a three-dimensional perspective to the presentation. Welcome to the Semantic Web as seen through the eyes of a Virtual World participant, an environment where Web users no longer are browsing for information that is largely static, where Web users interact through their proxies (avatars) query applications (Web agents) soliciting them to collect, filter, verify, correlate and present answers to their queries often in a more visually palatable three-dimensional format. Following a brief overview of these two technologies, this article presents several of the key force drivers behind their evolution and the benefits gleaned from their collective use. Further discussion identifies new methods for visualizing semantic content in virtual worlds. Finally, as with any technological evolution, the merge of these two technologies brings on a whole new set of challenges from a Web userÕs perspective as well as perspectives from technology developers both in academia and government

SOCIAL MEDIA IN MODERN BUSINESS

Social media help companies to reach new customers. New areas where companies can use social media include web-based training, team-based projects, distribution of updates about plans and activities to employees, search for new offers and verification of information during staff recruitment. The purpose of this article is to identify possible trends in the use of social media for enhancing the performance of modern business ventures. This paper compares selected classifications of the Internet development phases. The rule of content cocreation and sharing, typical of Web 2.0, remains valid during the subsequent stage of development, i.e. Web 3.0. A qualitative difference consists in adding a new function of using semantic analysis of messages posted in the virtual space, most notably in the social media. Semantic analysis is applied primarily in order to adjust the products offered to consumers’ needs. Application of semantic tools may also be associated with information exclusion. This paper also analyzes the implications of semantic web in the new context, the effect of information extraction from the social media

A Focused Crawler in order to Get Semantic Web Resources (CSR)

This paper presents a Focused Crawler in order to Get Semantic Web Resources (CSR). Structured data web are available in formats such as Extensible Markup Language (XML), Resource Description Framework (RDF) and Ontology Web Language (OWL) that can be used for processing. One of the main challenges for performing a manual search and download semantic web resources is that this task consumes a lot of time. Our research work propose a focused crawler which allow to download these resources automatically and store them on disk in order to have a collection that will be used for data processing. CRS consists of three layers: (a) The User Interface Layer, (b) The Focus Crawler Layer and (c) The Base Crawler Layer. CSR uses as a selection policie the Shark-Search method. CSR was conducted with two experiments. The first one starts on December 15 2012 at 7:11 am and ends on December 16 2012 at 4:01 were obtained 448,123,537 bytes of data. The CSR ends by itself after to analyze 80,4375 seeds with an unlimited depth. CSR got 16,576 semantic resources files where the 89 % was RDF, the 10 % was XML and the 1% was OWL. The second one was based on the Web Data Commons work of the Research Group Data and Web Science at the University of Mannheim and the Institute AIFB at the Karlsruhe Institute of Technology. This began at 4:46 am of June 2 2013 and 1:37 am June 9 2013. After 162.51 hours of execution the result was 285,279 semantic resources where predominated the XML resources with 99 % and OWL and RDF with 1 % each one

Personal eBanking Solutions Based on Semantic Web Services

We describe how Semantic Web Service technology can be used for the provision of personal e-banking online services. We describe two deployed applications: an overdraft notification service and a mortgage comparison service. The former accesses the bank accounts of a user as well as utility goods Web sites where invoicing information is stored and estimates whether the user will be in an overdraft situation in the near future, alerting him/her by e-mail or SMS. The latter accesses the mortgage information provided by the heterogeneous Web sites of different banks and allows users to compare them according to different types of criteria. The chapter not only focuses on the technological decisions followed to implement and deploy these services, but also on the added value of applying Semantic Web Services for them

WEDGE: Web-Image Assisted Domain Generalization for Semantic Segmentation

Domain generalization for semantic segmentation is highly demanded in real applications, where a trained model is expected to work well in previously unseen domains. One challenge lies in the lack of data which could cover the diverse distributions of the possible unseen domains for training. In this paper, we propose a WEb-image assisted Domain GEneralization (WEDGE) scheme, which is the first to exploit the diversity of web-crawled images for generalizable semantic segmentation. To explore and exploit the real-world data distributions, we collect a web-crawled dataset which presents large diversity in terms of weather conditions, sites, lighting, camera styles, etc. We also present a method which injects the style representation of the web-crawled data into the source domain on-the-fly during training, which enables the network to experience images of diverse styles with reliable labels for effective training. Moreover, we use the web-crawled dataset with predicted pseudo labels for training to further enhance the capability of the network. Extensive experiments demonstrate that our method clearly outperforms existing domain generalization techniques