http://hdl.handle.net/10379/385 Sun, 29 Oct 2017 22:44:23 GMT 2017-10-29T22:44:23Z http://hdl.handle.net/10379/5560 Targeting online communities to maximise information diffusion Belák, Václav; Lam, Samantha; Hayes, Conor In recent years, many companies have started to utilise online social communities as a means of communicating with and targeting their employees and customers. Such online communities include discussion fora which are driven by the conversational activity of users. For example, users may respond to certain ideas as a result of the influence of their neighbours in the underlying social network. We analyse such influence to target communities rather than individual actors because information is usually shared with the community and not just with individual users. In this paper, we study information diffusion across communities and argue that some communities are more suitable for maximising spread than others. In order to achieve this, we develop a set of novel measures for cross-community influence, and show that it outperforms other targeting strategies on 51 weeks of data of the largest Irish online discussion system, Boards.ie. Sun, 01 Apr 2012 00:00:00 GMT http://hdl.handle.net/10379/5560 2012-04-01T00:00:00Z http://hdl.handle.net/10379/5392 Life-cycles and mutual effects of scientific communities Belák, Václav; Karnstedt, Marcel; Hayes, Conor Cross-community effects on the behaviour of individuals and communities themselves can be observed in a wide range of applications. While previous work has tried to explain and analyse such phenomena, there is still a great potential for increasing the quality and accuracy of this analysis. In this work, we propose a general framework consisting of several different techniques to analyse and explain cross-community effects and the underlying dynamics. The proposed methodology works with arbitrary community algorithms, incorporates meta-data to improve the overall quality and expressiveness of the analysis and identifies particular phenomena in an automated manner. We illustrate the benefits and strengths of our approach by exposing in-depth details of cross-community effects between two closely related and well established areas of scientific research. This work focuses on techniques for understanding, defining and eventually predicting typical life-cycles and events in the context of cross-community dynamics. Sat, 01 Jan 2011 00:00:00 GMT http://hdl.handle.net/10379/5392 2011-01-01T00:00:00Z http://hdl.handle.net/10379/4841 Cataloguing and Linking Life Sciences LOD Hasnain, Ali; Fox, Ronan; Deus, Helena F.; Decker, Stefan The Life Sciences Linked Open Data (LSLOD) Cloud is currently comprised of multiple datasets that add high value to biomedical research. The ability to navigate through these datasets in order to derive and discover new meaningful biological correlations is considered one of the most significant resources for supporting clinical decision making . However, navigating these multiple datasets is not easy as most of them are fragmented across multipleSPARQL endpoints, each containing trillions of triples and represented with insufficient vocabulary reuse. To retrieve and match, from multiple endpoints, the data required to answer meaningful biological questions, it is first necessary to catalogue the data represented in each endpoint, in order to understand how powerful queries traversing several SPARQL endpoints can be assembled. In this report, we explore the schema used to represent data from a total of 52 meaningful Life Sciences SPARQL endpoints and present our methodology for linking related concepts and properties from the pool of available elements. We found the outcome of this exploratory work not onlyto be helpful in identifying redundancy and gaps in the data, but also for enabling the assembly of complex federated queries. In this report we present three different approaches used to weave concepts and properties and discuss their applicability for creating complex links in the LSLOD cloud. Keywords: Linked Open Data, SPARQL, Life Sciences, Query Element . Conference paper Sun, 01 Jan 2012 00:00:00 GMT http://hdl.handle.net/10379/4841 2012-01-01T00:00:00Z http://hdl.handle.net/10379/4659 Reconstruction of Threaded Conversations in Online Discussion Forums Aumayr, Erik; Jeffrey, Chan; Hayes, Conor [no abstract available] Conference paper Mon, 18 Jul 2011 00:00:00 GMT http://hdl.handle.net/10379/4659 2011-07-18T00:00:00Z