Morphable Word Clouds for Time-Varying Text Data Visualization

2015 ◽  
Vol 21 (12) ◽  
pp. 1415-1426 ◽  
Author(s):  
Ming-Te Chi ◽  
Shih-Syun Lin ◽  
Shiang-Yi Chen ◽  
Chao-Hung Lin ◽  
Tong-Yee Lee
Keyword(s):  
Data Visualization ◽  
Time Varying ◽  
Text Data ◽  
Word Clouds

Effectiveness of Feature-Driven Storytelling in 3D Time-Varying Data Visualization

2017 ◽  
Vol 2017 (1) ◽  
pp. 99-109
Author(s):  
Li Yu ◽  
Lane Harrison ◽  
Aidong Lu
Keyword(s):  
Data Visualization ◽  
Time Varying

scholarly journals An Enhanced Approach for Using Data Visualization for Sentiment Analysis and Auto Summarization Data

2018 ◽  
Vol 12 (9) ◽  
pp. 190
Author(s):  
Osama Mohammad Rababah ◽  
Esra F. Alzaghoul ◽  
Hussam N. Fakhouri
Keyword(s):  
Sentiment Analysis ◽  
Data Visualization ◽  
Full Text ◽  
Visual Representation ◽  
The Other ◽  
The Internet ◽  
Original Text ◽  
Text Data ◽  
Data Summarization ◽  
Using Data

With the rapid increase in the size of the data over the internet there is a need for new studies for text data summarization and representation; rather than storing the full text or reading the full text we can store and read a summary that represent the original text. Furthermore, there is a need also to represent the summarized text with visual representation; one picture worth ten thousandwords. In this paper we propose an approach for visual representation of the summarized text;visual resources give creative control over how message is perceived andprovide a faster way to know what where the text about.This approach were implemented and tested on a sample of two datasets one of 50 texts and the other dataset of 80 positive and negative movie comments, the evaluation has been done visually and the percent of success cases has been reported, the precision and recall has been calculated.

Time-Varying Data Visualization Using Clustered Heatmap and Dual Scatterplots

2016 ◽  
Author(s):  
Satsuki Kumatani ◽  
Takayuki Itoh ◽  
Yousuke Motohashi ◽  
Keisuke Umezu ◽  
Masahiro Takatsuka
Keyword(s):  
Data Visualization ◽  
Time Varying

Using Data Visualization to Analyze Grade Crossing Accidents

2015 ◽  
Author(s):  
Trefor Williams ◽  
James Abello ◽  
John Betak ◽  
David Desimone
Keyword(s):  
Data Visualization ◽  
Time Varying ◽  
Visualization System ◽  
Railroad Industry ◽  
Accident Data ◽  
Pedestrian Accidents ◽  
Grade Crossing ◽  
Grade Crossings ◽  
Using Data ◽  
Visualization Techniques

The Federal Railroad Administration grade crossing accident database contains numerous interrelated variables. Understanding of how the variables are interrelated can be enhanced using modern visualization techniques. These techniques can allow managers from railroads and government agencies to find complex variables relationships not usually provided by routine statistical analyses. For this research we have developed several dashboards of linked visualizations using the Weave data visualization software [5]. Our visualizations explore various accident types of concern to the railroad industry including trespassing and pedestrian accidents, passenger train accidents, actions of highway users involved in accidents, and the effect of different types of warning devices on grade crossing accidents. In addition, we are currently developing an advanced visualization system that views the accident data as time varying events occurring over a fixed grade crossings topology. This view allows the application of a recent network data abstraction termed “Graph Cards.” We present initial examples of the advanced system that provides a variety of filtering mechanisms to view statistical distributions and their time varying behavior over the grade crossings topology.

scholarly journals VINCENT: A visual analytics system for investigating the online vaccine debate

2019 ◽  
Vol 11 (2) ◽  
Author(s):  
Anton Ninkov ◽  
Kamran Sedig
Keyword(s):  
Public Health ◽  
Natural Language Processing ◽  
Natural Language ◽  
Data Visualization ◽  
Language Processing ◽  
Visual Analytics ◽  
Complex Data ◽  
Text Data ◽  
Human Data ◽  
Vaccine Debate

This paper reports and describes VINCENT, a visual analytics system that is designed to help public health stakeholders (i.e., users) make sense of data from websites involved in the online debate about vaccines. VINCENT allows users to explore visualizations of data from a group of 37 vaccine-focused websites. These websites differ in their position on vaccines, topics of focus about vaccines, geographic location, and sentiment towards the efficacy and morality of vaccines, specific and general ones. By integrating webometrics, natural language processing of website text, data visualization, and human-data interaction, VINCENT helps users explore complex data that would be difficult to understand, and, if at all possible, to analyze without the aid of computational tools.The objectives of this paper are to explore A) the feasibility of developing a visual analytics system that integrates webometrics, natural language processing of website text, data visualization, and human-data interaction in a seamless manner; B) how a visual analytics system can help with the investigation of the online vaccine debate; and C) what needs to be taken into consideration when developing such a system. This paper demonstrates that visual analytics systems can integrate different computational techniques; that such systems can help with the exploration of public health online debates that are distributed across a set of websites; and that care should go into the design of the different components of such systems. 

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