1,179,562 research outputs found
Social Web Communities
Blogs, Wikis, and Social Bookmark Tools have rapidly emerged onthe Web. The reasons for their immediate success are that people are happy to share information, and that these tools provide an infrastructure for doing so without requiring any specific skills. At the moment, there exists no foundational research for these systems, and they provide only very simple structures for organising knowledge. Individual users create their own structures, but these can currently not be exploited for knowledge sharing. The objective of the seminar was to provide theoretical foundations for upcoming Web 2.0 applications and to investigate further applications that go beyond bookmark- and file-sharing.
The main research question can be summarized as follows: How will current and emerging resource sharing systems support users to leverage more knowledge and power from the information they share on Web 2.0 applications? Research areas like Semantic Web, Machine Learning, Information Retrieval, Information Extraction, Social Network Analysis, Natural Language Processing, Library and Information Sciences, and Hypermedia Systems have been working for a while on these questions. In the workshop, researchers from these areas came together to assess the state of the art and to set up a road map describing the next steps
towards the next generation of social software
Social Web Communities
Blogs, Wikis, and Social Bookmark Tools have rapidly emerged on the Web. The reasons for their immediate success are that people are happy to share information, and that these tools provide an infrastructure for doing so without requiring any specific skills. At the moment, there exists no foundational research for these systems, and they provide only very simple structures for organising knowledge. Individual users create their own structures, but these can currently not be exploited for knowledge sharing. The objective of the seminar was to provide theoretical foundations for upcoming Web 2.0 applications and to investigate further applications that go beyond bookmark- and file-sharing. The main research question can be summarized as follows: How will current and emerging resource sharing systems support users to leverage more knowledge and power from the information they share on Web 2.0 applications? Research areas like Semantic Web, Machine Learning, Information Retrieval, Information Extraction, Social Network Analysis, Natural Language Processing, Library and Information Sciences, and Hypermedia Systems have been working for a while on these questions. In the workshop, researchers from these areas came together to assess the state of the art and to set up a road map describing the next steps towards the next generation of social software
Discovering New Sentiments from the Social Web
A persistent challenge in Complex Systems (CS) research is the
phenomenological reconstruction of systems from raw data. In order to face the
problem, the use of sound features to reason on the system from data processing
is a key step. In the specific case of complex societal systems, sentiment
analysis allows to mirror (part of) the affective dimension. However it is not
reasonable to think that individual sentiment categorization can encompass the
new affective phenomena in digital social networks.
The present papers addresses the problem of isolating sentiment concepts
which emerge in social networks. In an analogy to Artificial Intelligent
Singularity, we propose the study and analysis of these new complex sentiment
structures and how they are similar to or diverge from classic conceptual
structures associated to sentiment lexicons. The conjecture is that it is
highly probable that hypercomplex sentiment structures -not explained with
human categorizations- emerge from high dynamic social information networks.
Roughly speaking, new sentiment can emerge from the new global nervous systems
as it occurs in humans
The institutional character of computerized information systems
We examine how important social and technical choices become part of the history of a computer-based information system (CB/SJ and embedded in the social structure which supports its development and use. These elements of a CBIS can be organized in specific ways to enhance its usability and performance. Paradoxically, they can also constrain future implementations and post-implementations.We argue that CBIS developed from complex, interdependent social and technical choices should be conceptualized in terms of their institutional characteristics, as well as their information-processing characteristics. The social system which supports the development and operation of a CBIS is one major element whose institutional characteristics can effectively support routine activities while impeding substantial innovation. Characterizing CBIS as institutions is important for several reasons: (1) the usability of CBIS is more critical than the abstract information-processing capabilities of the underlying technology; (2) CBIS that are well-used and have stable social structures are more difficult to replace than those with less developed social structures and fewer participants; (3) CBIS vary from one social setting to another according to the ways in which they are organized and embedded in organized social systems. These ideas are illustrated with the case study of a failed attempt to convert a complex inventory control system in a medium-sized manufacturing firm
Building ontologies from folksonomies and linked data: Data structures and Algorithms
We present the data structures and algorithms used in the approach for building domain ontologies from folksonomies and linked data. In this approach we extracts domain terms from folksonomies and enrich them with semantic information from the Linked Open Data cloud. As a result, we obtain a domain ontology that combines the emergent knowledge of social tagging systems with formal knowledge from Ontologies
Multilevel compression of random walks on networks reveals hierarchical organization in large integrated systems
To comprehend the hierarchical organization of large integrated systems, we
introduce the hierarchical map equation, which reveals multilevel structures in
networks. In this information-theoretic approach, we exploit the duality
between compression and pattern detection; by compressing a description of a
random walker as a proxy for real flow on a network, we find regularities in
the network that induce this system-wide flow. Finding the shortest multilevel
description of the random walker therefore gives us the best hierarchical
clustering of the network, the optimal number of levels and modular partition
at each level, with respect to the dynamics on the network. With a novel search
algorithm, we extract and illustrate the rich multilevel organization of
several large social and biological networks. For example, from the global air
traffic network we uncover countries and continents, and from the pattern of
scientific communication we reveal more than 100 scientific fields organized in
four major disciplines: life sciences, physical sciences, ecology and earth
sciences, and social sciences. In general, we find shallow hierarchical
structures in globally interconnected systems, such as neural networks, and
rich multilevel organizations in systems with highly separated regions, such as
road networks.Comment: 11 pages, 5 figures. For associated code, see
http://www.tp.umu.se/~rosvall/code.htm
Outline of a multilevel approach of the network society
Social and media networks, the Internet in particular, increasingly link interpersonal, organizational and mass communication. It is argued that this gives a cause for an interdisciplinary and multilevel approach of the network society. This will have to link traditional micro- and meso-level research of social and communication ties (Rogers, Granovetter a.o.) to the macro-level research of the network society at large (Castells a.o.).\ud
Systems theory linked to a theory of communicative action establishes a potential basis for a multilevel theory. The systems theory described uses elements of a biologically inspired analysis of networks as complex adaptive systems and the mathematically inspired theory of random and scale-free networks recently elaborated by Barabási, Strogatz and Watts. The outline of the multilevel theory is summarized in ten statements about changing relationships in the network society: an information society with structures and modes of organization primarily shaped by social and media networks. \ud
In the last section an inventory is made of the theoretical and methodological changes communication science will have to make to develop a general theory of the information and the network society in the perspective of communication
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