Text Analytics for Android Project

Most advanced text analytics and text mining tasks include text classification, text clustering, building ontology, concept/entity extraction, summarization, deriving patterns within the structured data, production of granular taxonomies, sentiment and emotion analysis, document summarization, entity relation modelling, interpretation of the output. Already existing text analytics and text mining cannot develop text material alternatives (perform a multivariant design), perform multiple criteria analysis, automatically select the most effective variant according to different aspects (citation index of papers (Scopus, ScienceDirect, Google Scholar) and authors (Scopus, ScienceDirect, Google Scholar), Top 25 papers, impact factor of journals, supporting phrases, document name and contents, density of keywords), calculate utility degree and market value. However, the Text Analytics for Android Project can perform the aforementioned functions. To the best of the knowledge herein, these functions have not been previously implemented; thus this is the first attempt to do so. The Text Analytics for Android Project is briefly described in this article

Using self-categorization theory to uncover the framing of the 2015 Rugby World Cup: a cross-cultural comparison of three nations’ newspapers

Research into the framing of sporting events has been extensively studied to uncover newspaper bias in the coverage of global sporting events. Through discourse, the media attempt to capture, build, and maintain audiences for the duration of sporting events through the use of multiple narratives and/or storylines. Little research has looked at the ways in which the same event is reported across different nations, and media representations of the Rugby World Cup have rarely featured in discussions of the framing of sport events. The present study highlights the different ways in which rugby union is portrayed across the three leading Southern Hemisphere nations in the sport. It also shows the prominence of nationalistic discourse across those nations and importance of self-categorizations in newspaper narratives.</jats:p

Random acts of violins : Oliver Schroer and two British Columbia fiddle communities

Publisher PD

Finding the Signal in the Noise: Information Governance, Analytics, and the Future of Legal Practice

In the watershed year of 2012, the world of law witnessed the first concrete discussion of how predictive analytics may be used to make legal practice more efficient. That the conversation about the use of predictive analytics has emerged out of the e-Discovery sector of the law is not all that surprising: in the last decade and with increasing force since 2006— with the passage of revised Federal Rules of Civil Procedure that expressly took into account the fact that lawyers must confront “electronically stored information” in all its varieties—there has been a growing recognition among courts and commentators that the practice of litigation is changing dramatically. What needs now to be recognized, however, is that the rapidly evolving tools and techniques that have been so helpful in providing efficient responses to document requests in complex litigation may be used in a variety of complementary ways to the discovery process itself

Overcoming the Digital Tsunami in e-Discovery: is Visual Analysis the Answer?

New technologies are generating potentially discoverable evidence in electronic form in ever increasing volumes. As a result, traditional techniques of document search and retrieval in pursuit of electronic discovery in litigation are becoming less viable. One potential new technological solution to the e-discovery search and retrieval challenge is Visual Analysis (VA). VA is a technology that combines the computational power of the computer with graphical representations of large datasets to enable interactive analytic capabilities. This article provides an overview of VA technology and how it is being applied in the analysis of e-mail and other electronic documents in the field of e-discovery, as well as discussing several challenges and limitations of the technology. The article concludes that VA has the potential to overcome some of the limitations of current search and retrieval techniques, but that addressing the digital tsunami is more likely to be achieved by using VA in combination with other search and retrieval technologies in the context of creating an effective data governance program

Using Technology Enabled Qualitative Research to Develop Products for the Social Good, An Overview

This paper discusses the potential benefits of the convergence of three recent trends for the design of socially beneficial products and services: the increasing application of qualitative research techniques in a wide range of disciplines, the rapid mainstreaming of social media and mobile technologies, and the emergence of software as a service. Presented is a scenario facilitating the complex data collection, analysis, storage, and reporting required for the qualitative research recommended for the task of designing relevant solutions to address needs of the underserved. A pilot study is used as a basis for describing the infrastructure and services required to realize this scenario. Implications for innovation of enhanced forms of qualitative research are presented

Telling Our Own Story: The Role of Narrative in Racial Healing

An important resource for leaders and practitioners working to overcome our nation's legacy of racism. The authors present the power of the narrative and its important role in racial healing

Lexical typology through similarity semantics: Toward a semantic map of motion verbs

This paper discusses a multidimensional probabilistic semantic map of lexical motion verb stems based on data collected from parallel texts (viz. translations of the Gospel according to Mark) for 100 languages from all continents. The crosslinguistic diversity of lexical semantics in motion verbs is illustrated in detail for the domain of `go', `come', and `arrive' type contexts. It is argued that the theoretical bases underlying probabilistic semantic maps from exemplar data are the isomorphism hypothesis (given any two meanings and their corresponding forms in any particular language, more similar meanings are more likely to be expressed by the same form in any language), similarity semantics (similarity is more basic than identity), and exemplar semantics (exemplar meaning is more fundamental than abstract concepts)

Catching the Banksters: The Use of Big Data Analytics in Billion Dollar Regulatory Investigations

Following the financial crisis, emboldened regulators have increased the magnitude of fines levied for financial malfeasance. The automation of the data discovery process underpins the rise in internal investigations, which financial organizations are obliged to conduct on the behest of regulators, keen to reduce information asymmetries and bolster transparency. Yet little research exists into the technologies which underpin post-crisis regulatory agendas. Our study focuses on big data technologies (eDiscovery tools) which facilitate investigations, where rare yet serious breaches have occurred. We focus on the micro/data level (volume, veracity, variety and velocity) to understand how these tools are influencing regulatory outcomes. The findings illustrate the need for financial organizations to adopt robust information governance policies to ease future investigatory efforts. We identify various practices which may help compliance managers better respond to regulatory investigations faster and more easily to ease the burden of post-crisis regulation