Capturing Emergent Semantics from Social Annotation Systems

The ongoing growth of the World Wide Web, catalyzed by the increasing possibility of ubiquitous access via a variety of devices, continues to strengthen its role as our prevalent information and commmunication medium. However, although tools like search engines facilitate retrieval, the task of finally making sense of Web content is still often left to human interpretation. The vision of supporting both humans and machines in such knowledge-based activities led to the development of different systems which allow to structure Web resources by metadata annotations. Interestingly, two major approaches which gained a considerable amount of attention are addressing the problem from nearly opposite directions: On the one hand, the idea of the Semantic Web suggests to formalize the knowledge within a particular domain by means of the "top-down" approach of defining ontologies. On the other hand, Social Annotation Systems as part of the so-called Web 2.0 movement implement a "bottom-up" style of categorization using arbitrary keywords. Experience as well as research in the characteristics of both systems has shown that their strengths and weaknesses seem to be inverse: While Social Annotation suffers from problems like, e. g., ambiguity or lack or precision, ontologies were especially designed to eliminate those. On the contrary, the latter suffer from a knowledge acquisition bottleneck, which is successfully overcome by the large user populations of Social Annotation Systems. Instead of being regarded as competing paradigms, the obvious potential synergies from a combination of both motivated approaches to "bridge the gap" between them. These were fostered by the evidence of emergent semantics, i. e., the self-organized evolution of implicit conceptual structures, within Social Annotation data. While several techniques to exploit the emergent patterns were proposed, a systematic analysis - especially regarding paradigms from the field of ontology learning - is still largely missing. This also includes a deeper understanding of the circumstances which affect the evolution processes. This work aims to address this gap by providing an in-depth study of methods and influencing factors to capture emergent semantics from Social Annotation Systems. We focus hereby on the acquisition of lexical semantics from the underlying networks of keywords, users and resources. Structured along different ontology learning tasks, we use a methodology of semantic grounding to characterize and evaluate the semantic relations captured by different methods. In all cases, our studies are based on datasets from several Social Annotation Systems. Specifically, we first analyze semantic relatedness among keywords, and identify measures which detect different notions of relatedness. These constitute the input of concept learning algorithms, which focus then on the discovery of synonymous and ambiguous keywords. Hereby, we assess the usefulness of various clustering techniques. As a prerequisite to induce hierarchical relationships, our next step is to study measures which quantify the level of generality of a particular keyword. We find that comparatively simple measures can approximate the generality information encoded in reference taxonomies. These insights are used to inform the final task, namely the creation of concept hierarchies. For this purpose, generality-based algorithms exhibit advantages compared to clustering approaches. In order to complement the identification of suitable methods to capture semantic structures, we analyze as a next step several factors which influence their emergence. Empirical evidence is provided that the amount of available data plays a crucial role for determining keyword meanings. From a different perspective, we examine pragmatic aspects by considering different annotation patterns among users. Based on a broad distinction between "categorizers" and "describers", we find that the latter produce more accurate results. This suggests a causal link between pragmatic and semantic aspects of keyword annotation. As a special kind of usage pattern, we then have a look at system abuse and spam. While observing a mixed picture, we suggest that an individual decision should be taken instead of disregarding spammers as a matter of principle. Finally, we discuss a set of applications which operationalize the results of our studies for enhancing both Social Annotation and semantic systems. These comprise on the one hand tools which foster the emergence of semantics, and on the one hand applications which exploit the socially induced relations to improve, e. g., searching, browsing, or user profiling facilities. In summary, the contributions of this work highlight viable methods and crucial aspects for designing enhanced knowledge-based services of a Social Semantic Web.

The social dimension: a neglected policy item in the Bologna Process

Since its beginning in 1999, the Bologna Process has influenced various aspects of higher education in its member countries, e.g., degree structures, mobility, lifelong learning, social dimension and quality assurance. The social dimension creates the focus of this research. The social dimension entered the Bologna Process agenda in 2001. Despite a decade of reforms, it somehow remained as a vague element and received low scholarly attention. This research addresses to this gap. Firstly, different meanings of the social dimension according to the major European policy actors are analysed. Unfolding the understandings of the actors revealed that the social dimension is mostly understood in terms reflecting the diversity of population on the student body accessing to, progressing in and completing higher education, with a special concern on the underrepresented groups. However, it is not possible to observe a similar commonality concerning the actual policy measures to achieve this goal. Divergence occurs with respect to the addressed underrepresented groups, i.e., all underrepresented groups or people without formal qualifications and mature learners, and the values and institutional interests traditionally promoted by these actors. Secondly, the dissertation discusses the reflection of this social dimension understanding at the national level by looking at cases of Finland, Germany and Turkey. The in-depth analyses show an awareness of the social dimension among most of the national Bologna Process actors and a common understanding of the social dimension goals. However, this understanding has not triggered action in any of the countries. The countries acted on areas which they defined problematic before the Bologna Process. Finally, based on these findings the dissertation discusses the social dimension as a policy item that managed to get into the Bologna Process agenda, but neither grew into an implementable policy, nor drop out of it. To this aim, it makes use of the multiple streams framework and explains the low agenda status social dimension with: i. the lack of a pressing problem definition: the lack of clearly defined indicators and a comprehensive monitoring system, ii. the lack of a viable solution alternative: the proposal of developing national strategies and action plans closed the way to develop generic guidelines for the social dimension to be translated into national policy processes, iii. low political perceptivity: the recent trends opt for increasing efficiency, excellence and exclusiveness discourses rather than ensuring equality and inclusiveness iv. high constraints: the social dimension by definition requires more public funding which is less appreciated and strategic constraints of the actors in allocating their resources v. the type of policy entrepreneur: the social dimension is promoted by an international stakeholder, the European Students’ Union, instead of the ministers responsible for higher education The social dimension remains a policy item in the Bologna Process which is noble enough to agree but not urgent enough to act on.

Social Inequality and Social Policy outside the OECD

Almost all Latin American countries are still marked by extreme forms of social inequality – and to an extent, this seems to be the case regardless of national differences in the economic development model or the strength of democracy and the welfare state. Recent research highlights the fact that the heterogeneous labour markets in the region are a key source of inequality. At the same time, there is a strengthening of ‘exclusive’ social policy, which is located at the fault lines of the labour market and is constantly (re-)producing market-mediated disparities. In the last three decades, this type of social policy has even enjoyed democratic legitimacy. These dynamics challenge many of the assumptions guiding social policy and democratic theory, which often attempt to account for the specificities of the region by highlighting the purported flaws of certain policies. We suggest taking a different perspective: social policy in Latin American should not be grasped as a deficient or flawed type of social policy, but as a very successful relation of political domination. ‘Relational social analysis’ locates social policy in the ‘tension zone’ constituted by the requirements of economic reproduction, demands for democratic legitimacy and the relative autonomy of the state. From this vantage point, we will make the relation of domination in question accessible for empirical research. It seems particularly useful for this purpose to examine the recent shifts in the Latin American labour markets, which have undergone numerous reforms. We will examine which mechanisms, institutions and constellations of actors block or activate the potentials of redistribution inherent in such processes of political reform. This will enable us to explore the socio-political field of forces that has been perpetuating the social inequalities in Latin America for generations.