Data Mining; A Conceptual Overview

This tutorial provides an overview of the data mining process. The tutorial also provides a basic understanding of how to plan, evaluate and successfully refine a data mining project, particularly in terms of model building and model evaluation. Methodological considerations are discussed and illustrated. After explaining the nature of data mining and its importance in business, the tutorial describes the underlying machine learning and statistical techniques involved. It describes the CRISP-DM standard now being used in industry as the standard for a technology-neutral data mining process model. The paper concludes with a major illustration of the data mining process methodology and the unsolved problems that offer opportunities for research. The approach is both practical and conceptually sound in order to be useful to both academics and practitioners

A preliminary proposal of a conceptual Educational Data Mining framework for Science Education: Scientific competences development and self-regulated learning

The present paper is part of a wider study, focussed on the development of a digital educational resource for Science Education in primary school, integrating an Educational Data Mining framework. The proposed conceptual framework aims to infer the impact of the adopted learning approach for the development of scientific competences and students’ self-regulated learning. Thus, students’ exploration of learning sequences and students' behaviour towards available help, formative feedback and recommendations will be analysed. The framework derives from the proposed learning approach, as well as from the literature review. Before introducing it, the authors present an overview of the digital educational resource learning approach and the adopted Educational Data Mining methods. Finally, we present the proposed conceptual Educational Data Mining framework for Science Education, focussing its relevance on the development of students' scientific competences and self-regulated learning.publishe

Democratization beyond the post-democratic turn: towards a research agenda on new conceptions of citizen participation

Following extensive debates about post-democracy and post-politics, scholarly attention has shifted to conceptualizing the ongoing transformation of democracy. In this endeavour, the change in understandings, expectations and functions of political participation is a key parameter. Improving citizen participation is widely regarded as the hallmark of democratization. Yet, a variety of actors are also increasingly ambivalent about democratic institutions and the further expansion of participation. Meanwhile, new forms of participation are gaining in significance – neoliberal activation, the responsibilization of consumers, digital data mining, managed behaviour guided by choice architects – which some believe much improve representation, but which others perceive as a threat to the citizens’ autonomy. This article introduces a special issue focusing on the participation-democratization nexus in well-established democracies in the economically affluent global North. Based on a critical review of popular narratives of post-democracy and post-politics we sketch the notion of the post-democratic turn – which offers a new perspective on emerging forms of participation and in this special issue serves as a conceptual lens for their analysis. We then revisit more traditional conceptualizations of democratic participation which are challenged by the post-democratic turn. The article concludes with an overview of the individual contributions to this special issue

Big Data Analytics and the Social Web: a Tutorial for the Social Scientist

The social web or web 2.0 has become the biggest and most accessible repository of data about human (social) behavior in history. Due to a knowledge gap between big data analytics and established social science methodology, this enormous source of information, has yet to be exploited for new and interesting studies in various social and humanities related fields. To make one step towards closing this gap, we provide a detailed step-by-step tutorial on some of the most important web mining and analytics methods on a real-world study of Croatia’s biggest political blogging site. The tutorial covers methods for data retrieval, data conversion, cleansing and organization, data analysis (natural language processing, social and conceptual network analysis) as well as data visualization and interpretation. All tools that have been implemented for the sake of this study, data sets through the various steps as well as resulting visualizations have been published on-line and are free to use. The tutorial is not meant to be a comprehensive overview and detailed description of all possible ways of analyzing data from the social web, but using the steps outlined herein one can certainly reproduce the results of the study or use the same or similar methodology for other datasets. Results of the study show that a special kind of conceptual network generated by natural language processing of articles on the blogging site, namely a conceptual network constructed by the rule that two concepts (keywords) are connected if they were extracted from the same article, seem to be the best predictor of the current political discourse in Croatia when compared to the other constructed conceptual networks. These results indicate that a comprehensive study has to be made to investigate this conceptual structure further with an accent on the dynamic processes that have led to the construction of the network

A Spatial Decision Support System for Property Valuation

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Mining and development : examining the effectiveness of mining company community development intervention in New Ireland Province, Papua New Guinea : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Development Studies at Massey University, Manawatu, New Zealand

This thesis explores the effectiveness of mining company contributions to development within the gold mining communities of Lihir and Simberi islands, in New Ireland Province, Papua New Guinea (PNG). More specifically, it analyses the extent to which forms of community development intervention undertaken on Lihir Island by Newcrest Mining Ltd, and on Simberi Island by St Barbara Ltd, actually support meaningful forms of development. This has been achieved through the use of development ethics (Goulet 1995) as a conceptual research framework, which when applied in research practice, gives priority to the wellbeing of those whose realities may be ignored, misread or marginalised within the neoliberal realm of development. This research is based on a total of four months of fieldwork undertaken on Lihir and Simberi islands. It draws on community narratives to frame the relevance of human wellbeing, human rights and inclusive development as development ethics within the research context. This development ethics research lens facilitates discussion about the meaningfulness of development intervention from a morally-informed community development perspective. Underpinned by a locally contextualised appreciation of what human wellbeing and meaningful development means on Lihir and Simberi islands (which results in the exposition of a set of local Community Wellbeing and Development Rights), a critical review of the practice and governance of development intervention within each Island community is then detailed. The analysis of development interventions then proceeds using firstly an evaluation of practices within a human rights lens, and secondly consideration of inclusive development outcomes relative to Newcrest's and St Barbara’s development related rhetoric. The resulting account of mining company community development intervention is critical, but ultimately hopeful. This hopefulness reflects the hope of customary landowners that mining will one day lead to meaningful development benefits. The analysis from this development ethics lens reveals insights into the promotion of social justice through the delivery of mining company development interventions. It is argued that mining companies have the opportunity to enhance a set of locally significant and internationally recognised human rights that are important to the wellbeing and development of customary landowners. Although, in some instances, mining company performance is falling short with respect to the enhancement of these human rights, it is argued that the enhancement of Community Wellbeing and Development Rights exists as a potential means for mining companies to add value to host communities. However, if such a development programme is to be meaningful to customary landowners, it must also advance equity and fairness. If mining companies fail to navigate such complexities, this thesis contends that mining, and forms of mining company community development intervention, will likely do more harm to communities than good

Conceptual biology, hypothesis discovery, and text mining: Swanson's legacy

Innovative biomedical librarians and information specialists who want to expand their roles as expert searchers need to know about profound changes in biology and parallel trends in text mining. In recent years, conceptual biology has emerged as a complement to empirical biology. This is partly in response to the availability of massive digital resources such as the network of databases for molecular biologists at the National Center for Biotechnology Information. Developments in text mining and hypothesis discovery systems based on the early work of Swanson, a mathematician and information scientist, are coincident with the emergence of conceptual biology. Very little has been written to introduce biomedical digital librarians to these new trends. In this paper, background for data and text mining, as well as for knowledge discovery in databases (KDD) and in text (KDT) is presented, then a brief review of Swanson's ideas, followed by a discussion of recent approaches to hypothesis discovery and testing. 'Testing' in the context of text mining involves partially automated methods for finding evidence in the literature to support hypothetical relationships. Concluding remarks follow regarding (a) the limits of current strategies for evaluation of hypothesis discovery systems and (b) the role of literature-based discovery in concert with empirical research. Report of an informatics-driven literature review for biomarkers of systemic lupus erythematosus is mentioned. Swanson's vision of the hidden value in the literature of science and, by extension, in biomedical digital databases, is still remarkably generative for information scientists, biologists, and physicians. © 2006Bekhuis; licensee BioMed Central Ltd