44,556 research outputs found

    Distributed leadership, trust and online communities

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    This paper analyses the role of distributed leadership and trust in online communities. The team-based informal ethos of online collaboration requires a different kind of leadership from that in formal positional hierarchies. Such leadership may be more flexible and sophisticated, capable of encompassing ambiguity and rapid change. Online leaders need to be partially invisible, delegating power and distributing tasks. Yet, simultaneously, online communities are facilitated by the high visibility and subtle control of expert leaders. This paradox: that leaders need to be both highly visible and invisible as appropriate, was derived from prior research and tested in the analysis of online community discussions using a pattern-matching process. It is argued that both leader visibility and invisibility are important for the facilitation of trusting collaboration via distributed leadership. Advanced leadership responses to complex situations in online communities foster positive group interaction and decision-making, facilitated through active distribution of specific tasks

    Toward a Quantitative Analysis of Online Communities

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    In flexible learning environments there has been an increased focus on developing resources that promote and facilitate the emergence of online communities. The formation of, and active participation in, a learning community has been suggested to facilitate the learning process (Rovai, 2002; Palloff & Pratt, 1999). Current literature examining the formation and development of online communities has predominantly centred on the qualitative analysis of posted messages (within an asynchronous discussion forum) as evidence for community attainment and sustainment (Brook & Oliver, 2003; Hew & Cheung, 2003). The search for key words and phrases is conducted regardless of timing and position within the threaded discussion. Hence, analysis of the postings often occurs in a manner that de-contextualises the discourse throughout the delivery of a subject (Misanchuk & Dueber, 2001). Furthermore, as analysis is limited to a few disparate units of study, an overall picture of the extent to which the online communities formed in individual units are supporting the strategic goals of the university is not formed. Investment in online technologies and development of learning and teaching strategies is conducted at an enterprise level. However, current methodologies evaluating the development and sustainment of online communities have been focussed at a localised level. This paper proposes a scaleable quantitative approach to identify the degree of learner interactions occurring in specific subject-based forums for further qualitative analysis. It is proposed that the examination of data derived from the wider University context better positions and informs staff undertaking subject-based forums in order to align with University strategic goals

    Semantic Variation in Online Communities of Practice

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    We introduce a framework for quantifying semantic variation of common words in Communities of Practice and in sets of topic-related communities. We show that while some meaning shifts are shared across related communities, others are community-specific, and therefore independent from the discussed topic. We propose such findings as evidence in favour of sociolinguistic theories of socially-driven semantic variation. Results are evaluated using an independent language modelling task. Furthermore, we investigate extralinguistic features and show that factors such as prominence and dissemination of words are related to semantic variation.Comment: 13 pages, Proceedings of the 12th International Conference on Computational Semantics (IWCS 2017

    Measuring quality, reputation and trust in online communities

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    In the Internet era the information overload and the challenge to detect quality content has raised the issue of how to rank both resources and users in online communities. In this paper we develop a general ranking method that can simultaneously evaluate users' reputation and objects' quality in an iterative procedure, and that exploits the trust relationships and social acquaintances of users as an additional source of information. We test our method on two real online communities, the EconoPhysics forum and the Last.fm music catalogue, and determine how different variants of the algorithm influence the resultant ranking. We show the benefits of considering trust relationships, and define the form of the algorithm better apt to common situations

    Heterogeneity shapes groups growth in social online communities

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    Many complex systems are characterized by broad distributions capturing, for example, the size of firms, the population of cities or the degree distribution of complex networks. Typically this feature is explained by means of a preferential growth mechanism. Although heterogeneity is expected to play a role in the evolution it is usually not considered in the modeling probably due to a lack of empirical evidence on how it is distributed. We characterize the intrinsic heterogeneity of groups in an online community and then show that together with a simple linear growth and an inhomogeneous birth rate it explains the broad distribution of group members.Comment: 5 pages, 3 figure panel
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