Computational Argumentation Approaches to Improve Sensemaking and Evidence-based Reasoning in Online Deliberation Systems

Deliberation is the process through which communities identify potential solutions for a problem and select the solution that most effectively meets their diverse requirements through dialogic communication. Online deliberation is implemented nowadays with means of social media and online discussion platforms; however, these media present significant challenges and issues that can be traced to inadequate support for Sensemaking processes and poor endorsement of the quality characteristics of deliberation. This thesis investigates integrating computational argumentation methods in online deliberation platforms as an effective way to improve participants' perception of the quality of the deliberation process, their way of making sense of the overall process and producing healthier social dynamics. For that, two computational artefacts are proposed: (i) a Synoptical summariser of long discussions and (ii) a Scientific Argument Recommender System (SciArgRecSys). The two artefacts are designed and developed with state-of-the-art methods (with the use of Large Language Models - LLMs) and evaluated intrinsically and extrinsically when deployed in a real live platform (BCause). Through extensive evaluation, the positive effect of both artefacts is illustrated in human Sensemaking and essential quality characteristics of deliberation such as reciprocal Engagement, Mutual Understanding, and Social dynamics. In addition, it has been demonstrated that these interventions effectively reduce polarisation, the formation of sub-communities while significantly enhancing the quality of the discussion by making it more coherent and diverse

WiFi-Based Human Activity Recognition Using Attention-Based BiLSTM

Recently, significant efforts have been made to explore human activity recognition (HAR) techniques that use information gathered by existing indoor wireless infrastructures through WiFi signals without demanding the monitored subject to carry a dedicated device. The key intuition is that different activities introduce different multi-paths in WiFi signals and generate different patterns in the time series of channel state information (CSI). In this paper, we propose and evaluate a full pipeline for a CSI-based human activity recognition framework for 12 activities in three different spatial environments using two deep learning models: ABiLSTM and CNN-ABiLSTM. Evaluation experiments have demonstrated that the proposed models outperform state-of-the-art models. Also, the experiments show that the proposed models can be applied to other environments with different configurations, albeit with some caveats. The proposed ABiLSTM model achieves an overall accuracy of 94.03%, 91.96%, and 92.59% across the 3 target environments. While the proposed CNN-ABiLSTM model reaches an accuracy of 98.54%, 94.25% and 95.09% across those same environments

Reimagining criminology's public role :an inquiry into the relationship between criminological expertise and the democratic public sphere

PhD ThesisThis thesis contributes to recent discussions about criminology’s public role through an empirical case study analysis of the dominant discourse of ‘public confidence in the criminal justice system’ in England and Wales. The thesis begins by arguing that the recent literature reflecting on criminology’s public role has failed to adequately deal with the tensions created by the plural, value-dependent and contested character of criminological knowledge. Then, drawing on primary data from newspaper archives, parliamentary debates, research reports, academic books and papers, policy documents and focus group and interview transcripts, the thesis provides a multi-faceted analysis of the public confidence agenda. It argues that the dominant discourse of public confidence takes up a politically prominent ‘lay concept’ and, without clarifying what it means, discursively constructs it as a ‘real’ object which is both measurable and caused. This understanding of confidence reflects contingent historical conditions (including the ‘modernist’ criminological outlook), and is premised on an (unacknowledged) value-based decision about how to do research on how the public think and feel about the criminal justice system. The public confidence agenda in research and policy is a governmental project encompassing a double-epistemic aspiration: (i) to be epistemic (by providing scientific knowledge which shapes policy); and (ii) to promote a particular conception of criminological expertise (as episteme - objective, context-independent, scientific knowledge). As such it provides an excellent case study for reflecting on recent discussions of criminology’s public role. The thesis concludes that the starting point for any discussion of criminology’s public role in a democratic society should be an explicit acknowledgment of the value-based decisions which are implicit in every criminological project. Such acknowledgment provides a route to a more fruitful method for negotiating the inherent pluralism of the field, and thus to re-evaluating its public role.Knowledge Transfer Partnerships programme(KTP006241)and match-funded by the Economic and Social Research Council and the Northumbria Local Criminal Justice Boar

Re-engineering research and innovation information in university libraries in Uganda for small and medium enterprises.

Doctor of Philosophy in Information Studies. University of KwaZulu-Natal, Pietermaritzburg, 2019.Globally, enormous amounts of research are generated in universities; however, in Uganda, not much of this research cascades to Small and Medium Enterprises (SMEs) which contribute 75% of the nation’s Gross Domestic Product (GDP). Since university libraries are expected to support teaching, learning, research and community engagement in the surrounding communities, these libraries ought to reposition themselves to become conduits of disseminating Research and Innovation (R&I) to SMEs and other partners in development. The purpose of this study was to investigate how university libraries in Uganda can repackage R&I information and disseminate it to SMEs. The study addresses two broad objectives namely: 1) To investigate how University libraries in Uganda are facilitating access to R&I information for use by SMEs in the agricultural sector in Uganda; and 2) To find out the extent to which University libraries in Uganda repackage R&I information for use by SMEs in the agricultural sector. This study was underpinned by three theories namely: LibQUAL+TM, Modern theories of management and Wilson’s 1999 model of Information seeking behaviour. The study adopted a post-positivist research paradigm and an exploratory research design. Mixed methods epistemology was employed. Quantitative and qualitative data were therefore collected from a large sample of respondents from 6 universities that offer graduate agricultural programmes and from 231 SMEs in the agricultural sector. The respondents consisted of university librarians, heads of library research and innovation units, university heads of IT, Agricultural academic staff, graduate agricultural students and proprietors of SMEs in the agricultural sector in the central region of Uganda. Quantitative data was analysed using SPSS to generate descriptive and inferential statistics where frequencies, percentages and chi square were used, while the qualitative data was analysed through content analysis. The findings revealed that the research carried out in universities was beneficial to SMEs, mainly in areas of increasing the SMEs productivity, identifying training opportunities, and starting up new business ventures. A third of the respondents disclosed that currently Ugandan university libraries do not have an enabling environment for SMEs to access R&I information mainly because of inaccessible format in which R&I information is packaged. However, university libraries could re-engineer their R&I information services to serve SMEs mainly through digitisation, carrying out community engagement programmes targeting SMEs, and repackaging R&I information. The study among others recommended that R&I information should be repackaged from print to short documentaries, newsletters, using social media, translating it from English to local languages and broadcasting it on radios and televisions to make it suitable for SMEs