Combining social network analysis with semantic relations to support the evolution of a scientific community

Harrer, Andreas; Malzahn, Nils; Zeini, Sam; Hoppe, H. Ulrich

doi:10.3115/1599600.1599650

Cited by 11 publications

(16 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The results could be used for peer recommendation and the formation of learning groups (cf. Harrer et al, 2007). In blended learning scenarios, where learning activities take place in real-world as well as virtual environments, student groups based on resource access that are stable over time can be an indicator for group work in the real world.…”

Section: Resultsmentioning

confidence: 99%

“…The learners could interact indirectly mediated by those objects without necessarily having person-to-person communication. Social network analysis methods have also been applied to networks of people and artefacts to support the evolution of a knowledge-creating community in terms of the identification of people with common interests as well as trend analysis (Harrer et al, 2007). The work presented in Romero, Ventura, and García (2008) evaluates data-mining methods for resource usage of students in LMS including statistics, clustering, and classification.…”

Section: Analysis Methods For Learning Resource Usagementioning

confidence: 99%

“…Fini, 2009), focus on the production and sharing of knowledge artefacts like blogs or wiki articles by and between learners (Rodriguez, 2013). Apart from targeting a broad audience, the shift of learning activities into online environments can be of advantage even on smaller scale (Bruff et al, 2013;Harrer et al, 2007). Thus, "blended learning courses" provide hybrid approaches that combine the benefits of online learning and face-to-face sessions.…”

Section: The Role Of Learning Resources In Online Coursesmentioning

confidence: 99%

See 2 more Smart Citations

Analysis of Dynamic Resource Access Patterns in Online Courses

2014

View full text Add to dashboard Cite

This paper presents an analysis of resource access patterns in two recently conducted online courses. One of these has been a master level university lecture taught as a blended learning course with a wide range of online learning activities and materials, including collaborative wikis, self-tests, and thematic videos. The other course has been offered in the form of a MOOC. As a specialty of this course, master level students from two different universities could participate as a regular university class and receive credits for successful completion. In both courses, online learning resources such as videos, scientific literature, and wikis played a central role. In this context, the motivation for our research was to investigate characteristic patterns of resource usage of the learners. In order to gain deeper insights into the usage of learning materials, we have adapted methods from social network analysis and applied them to dynamic bipartite student-resource networks built from event logs of the students' resource access. In particular, we describe the clustering of students and resources in such networks and propose a method to identify patterns of the cluster evolution over time.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Analysis Methods For Learning Resource Usagementioning

confidence: 99%

Section: The Role Of Learning Resources In Online Coursesmentioning

confidence: 99%

See 1 more Smart Citation

Analysis of Dynamic Resource Access Patterns in Online Courses

2014

View full text Add to dashboard Cite

show abstract

“…Social network analysis (SNA) has been used in various areas, including computer-supported collaborative learning (Aviv, Erlich, Ravid, & Geva, 2003;de Laat, Lally, Lipponen, & Simons, 2007;Harrer, Malzahn, Zeini, & Hoppe, 2007;Reffay & Chanier, 2002). The basic approach relies on representing communication events as links between the actors in the network.…”

Section: Temporality Of a Learning Processmentioning

confidence: 99%

Analyzing the Main Paths of Knowledge Evolution and Contributor Roles in an Open Learning Community

Halatchliyski¹,

Hecking

Goehnert

et al. 2014

Learning Analytics

Self Cite

View full text Add to dashboard Cite

This paper introduces the scientometric method of main path analysis and its application in an exemplary study of the paths of knowledge development and the roles of contributors in Wikiversity. Data from two scientific domains in this online learning community has been used. We see this as a step forward in adapting and adopting network analysis techniques for analyzing collaboration processes in knowledge building communities. The analysis steps are presented in detail including the description of a tool environment ("workbench") designed for flexible use by non-computer experts. By identifying directed acyclic graphs, the meaningful interconnections between developing learning resources are analyzed by considering their temporal sequence. A schema for the visualization of the results is introduced. The potential of the method is elaborated for the evaluation of the overall learning process in different domains as well as for the individual contributions of the participants. Different outstanding roles of contributors in Wikiversity are presented and discussed.

show abstract

“…They extract different entity classes in texts, so the relations among the elements within and across any entity classes form certain types of networks. Finally, the combination of social network analysis with semantic networks has also been proposed in other works for ontology emergence and orientation (Harrer et al 2007, Mika 2007. In particular, Mika represents networks of folksonomies as a tripartite graph with hyper-edges considering the set of actors (users), the set of concepts (tags, keywords) and the set of objects annotated (bookmarks, photos, etc.).…”

Section: Introductionmentioning

confidence: 99%

A text categorisation tool for open source communities based on semantic analysis

Torres

Toral

Barrero

et al. 2013

Behaviour & Information Technology

View full text Add to dashboard Cite

Open source software (OSS) projects are supported by communities interacting through software repositories and mailing lists. Thousands of contributors participate in the development of the projects although they rarely meet each other. The result is a huge archived repository with thousands of questions, answers and contributions usually difficult to explore. We propose a tool based on semantic analysis for both performing an automatic knowledge discovery and a categorisation of the content of mailing lists repositories. Semantic analysis is a practical method for extracting and inferring relations of words in passages of discourse, producing measures of relations among words or passages that are well correlated with semantic similarity. The objective of this article is two-fold: (1) to develop a text categorisation tool based on indexing terms and semantic annotation, and (2) to apply the developed tool to extract the main dimensions related to knowledge sharing activities in virtual communities. Debian Linux ports to embedded processors are used as a case study to accomplish the proposed double objective.

show abstract

Combining social network analysis with semantic relations to support the evolution of a scientific community

Cited by 11 publications

References 8 publications

Analysis of Dynamic Resource Access Patterns in Online Courses

Analysis of Dynamic Resource Access Patterns in Online Courses

Analyzing the Main Paths of Knowledge Evolution and Contributor Roles in an Open Learning Community

A text categorisation tool for open source communities based on semantic analysis

Contact Info

Product

Resources

About