SAS Visual Text Analytics

2018 ◽  
pp. 263-282
Author(s):  
Murugan Anandarajan ◽  
Chelsey Hill ◽  
Thomas Nolan
Keyword(s):  
Text Analytics ◽  
Visual Text

scholarly journals Defragmenting Research Areas with Knowledge Visualization and Visual Text Analytics

2020 ◽  
Vol 10 (20) ◽  
pp. 7248
Author(s):  
Alejandro Benito-Santos ◽  
Roberto Therón Sánchez
Keyword(s):  
Computer Security ◽  
Communities Of Practice ◽  
Literature Analysis ◽  
Text Analytics ◽  
Sports Science ◽  
Research Areas ◽  
Wide Range ◽  
Common Interests ◽  
Visual Text ◽  
Visualization Techniques

The increasing specialization of science is motivating the fragmentation of traditional and well-established research areas into interdisciplinary communities of practice that focus on cooperation between experts to solve problems in a wide range of domains. This is the case of problem-driven visualization research (PDVR), in which groups of scholars use visualization techniques in different application domains such as the digital humanities, bioinformatics, sports science, or computer security. In this paper, we employ the findings obtained during the development of a novel visual text analytics tool we built in previous studies, GlassViz, to automatically detect interesting knowledge associations and groups of common interests between these communities of practice. Our proposed method relies on the statistical modeling of author-assigned keywords to make its findings, which are demonstrated in two use cases. The results show that it is possible to propose interactive, semisupervised visual approaches that aim at defragmenting a body of research using text-based, automatic literature analysis methods.

Seeing beyond reading: a survey on visual text analytics

2012 ◽  
Vol 2 (6) ◽  
pp. 476-492 ◽  
Author(s):  
Aretha B. Alencar ◽  
Maria Cristina F. de Oliveira ◽  
Fernando V. Paulovich
Keyword(s):  
Text Analytics ◽  
Visual Text

scholarly journals LitPathExplorer: a confidence-based visual text analytics tool for exploring literature-enriched pathway models

2017 ◽  
Vol 34 (8) ◽  
pp. 1389-1397 ◽  
Author(s):  
Axel J Soto ◽  
Chrysoula Zerva ◽  
Riza Batista-Navarro ◽  
Sophia Ananiadou
Keyword(s):  
Text Analytics ◽  
Pathway Models ◽  
Visual Text

scholarly journals GlassViz: Visualizing Automatically-Extracted Entry Points for Exploring Scientific Corpora in Problem-Driven Visualization Research

2020 ◽  
Author(s):  
Alejandro Benito-Santos ◽  
Roberto Theron
Keyword(s):  
Digital Humanities ◽  
Communication Channel ◽  
Interdisciplinary Communication ◽  
Cognitive Model ◽  
Proof Of Concept ◽  
Text Analytics ◽  
Research Papers ◽  
Proposed Model ◽  
Entry Points ◽  
Visual Text

In this paper, we report the development of a model and a proof-of-concept visual text analytics (VTA) tool to enhance document discovery in a problem-driven visualization research (PDVR) context. The proposed model captures the cognitive model followed by domain and visualization experts by analyzing the interdisciplinary communication channel as represented by keywords found in two disjoint collections of research papers. High distributional inter-collection similarities are employed to build informative keyword associations that serve as entry points to drive the exploration of a large document corpus. Our approach is demonstrated in the context of research on visualization for the digital humanities.

Interactive topic hierarchy revision for exploring a collection of online conversations

2018 ◽  
Vol 18 (3) ◽  
pp. 318-338 ◽  
Author(s):  
Enamul Hoque ◽  
Giuseppe Carenini
Keyword(s):  
Information Needs ◽  
User Study ◽  
Topic Model ◽  
Potential Utility ◽  
Text Analytics ◽  
Human In The Loop ◽  
Online Conversations ◽  
Visual Text ◽  
Promising Solution ◽  
Topic Hierarchy

In the last decade, there has been an exponential growth of asynchronous online conversations (e.g. blogs), thanks to the rise of social media. Analyzing and gaining insights from such discussions can be quite challenging for a user, especially when the user deals with hundreds of comments that are scattered around multiple different conversations. A promising solution to this problem is to automatically mine the major topics from conversations and organize them into a hierarchical structure. However, the resultant topic hierarchy can be noisy and/or it may not match the user’s current information needs. To address this problem, we introduce a novel human-in-the-loop approach that allows the user to revise the topic hierarchy based on her feedback. We incorporate this approach within a visual text analytics system that helps users in analyzing and getting insights from conversations by exploring and revising the topic hierarchy. We evaluated the resulting system with real users in a lab-based study. The results from the user study, when compared to its counterpart that does not support interactive revisions of a hierarchical topic model, provide empirical evidence of the potential utility of our system in terms of both performance and subjective measures. Finally, we summarize generalizable lessons for introducing human-in-the-loop computation within a visual text analytics system.

scholarly journals Prosumer Flexibility: A Comprehensive State-of-the-Art Review and Scientometric Analysis

Energies ◽  
2020 ◽  
Vol 13 (11) ◽  
pp. 2710 ◽  
Author(s):  
Matthew Gough ◽  
Sérgio F. Santos ◽  
Mohammed Javadi ◽  
Rui Castro ◽  
João P. S. Catalão
Keyword(s):  
Power Systems ◽  
State Of The Art ◽  
Scientometric Analysis ◽  
Supply Side ◽  
Text Analytics ◽  
Journal Articles ◽  
Detailed Understanding ◽  
Current State ◽  
Visual Text ◽  
Art Research

There is a growing need for increased flexibility in modern power systems. Traditionally, this flexibility has been provided by supply-side technologies. There has been an increase in the research surrounding flexibility services provided by demand-side actors and technologies, especially flexibility services provided by prosumers (those customers who both produce and consume electricity). This work gathers 1183 peer-reviewed journal articles concerning the topic and uses them to identify the current state of the art. This body of literature was analysed with two leading textual and scientometric analysis tools, SAS© Visual Text Analytics and VOSviewer, in order to provide a detailed understanding of the current state-of-the-art research on prosumer flexibility. Trends, key ideas, opportunities and challenges were identified and discussed.

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