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Full-Text Articles in Physical Sciences and Mathematics

Data-Driven Studies On Social Networks: Privacy And Simulation, Yasanka Sameera Horawalavithana Jun 2021

Data-Driven Studies On Social Networks: Privacy And Simulation, Yasanka Sameera Horawalavithana

USF Tampa Graduate Theses and Dissertations

Social media datasets are fundamental to understanding a variety of phenomena, such as epidemics, adoption of behavior, crowd management, and political uprisings. At the same time, many such datasets capturing computer-mediated social interactions are recorded nowadays by individual researchers or by organizations. However, while the need for real social graphs and the supply of such datasets are well established, the flow of data from data owners to researchers is significantly hampered by privacy risks: even when humans’ identities are removed, or data is anonymized to some extent, studies have proven repeatedly that re-identifying anonymized user identities (i.e., de-anonymization) is doable …


How Random Noise And A Graphical Convention Subverted Behavioral Scientists' Explanations Of Self-Assessment Data: Numeracy Underlies Better Alternatives, Edward Nuhfer, Steven Fleisher, Christopher Cogan, Karl Wirth, Eric Gaze Jan 2017

How Random Noise And A Graphical Convention Subverted Behavioral Scientists' Explanations Of Self-Assessment Data: Numeracy Underlies Better Alternatives, Edward Nuhfer, Steven Fleisher, Christopher Cogan, Karl Wirth, Eric Gaze

Numeracy

Despite nearly two decades of research, researchers have not resolved whether people generally perceive their skills accurately or inaccurately. In this paper, we trace this lack of resolution to numeracy, specifically to the frequently overlooked complications that arise from the noisy data produced by the paired measures that researchers employ to determine self-assessment accuracy. To illustrate the complications and ways to resolve them, we employ a large dataset (N = 1154) obtained from paired measures of documented reliability to study self-assessed proficiency in science literacy. We collected demographic information that allowed both criterion-referenced and normative-based analyses of self-assessment data. …


Infographics As Eye Candy: Review Of World War Ii In Numbers: An Infographic Guide To The Conflict, Its Conduct, And Its Casualties By Peter Doyle (2013), Joel Best Jan 2016

Infographics As Eye Candy: Review Of World War Ii In Numbers: An Infographic Guide To The Conflict, Its Conduct, And Its Casualties By Peter Doyle (2013), Joel Best

Numeracy

Peter Doyle. World War II in Numbers: An Infographic Guide to the Conflict, Its Conduct, and Its Casualties, illustrated by Lindsey Johns (Buffalo NY: Firefly Books, 2013). 224 pp. ISBN: 177085195X.

Doyle’s book contains dozens of graphs of statistical data dealing with World War II. Many of these graphs are visually striking. However, they often violate fundamental graphing principles, in that they distort quantitative relationships, use unidentified scales, and often make it difficult to compare quantities. Graphic software makes it easy to create imaginative images, but these can fail to communicate the very information that is the graph’s purpose.


Random Number Simulations Reveal How Random Noise Affects The Measurements And Graphical Portrayals Of Self-Assessed Competency, Edward Nuhfer, Christopher Cogan, Steven Fleisher, Eric Gaze, Karl Wirth Jan 2016

Random Number Simulations Reveal How Random Noise Affects The Measurements And Graphical Portrayals Of Self-Assessed Competency, Edward Nuhfer, Christopher Cogan, Steven Fleisher, Eric Gaze, Karl Wirth

Numeracy

Self-assessment measures of competency are blends of an authentic self-assessment signal that researchers seek to measure and random disorder or "noise" that accompanies that signal. In this study, we use random number simulations to explore how random noise affects critical aspects of self-assessment investigations: reliability, correlation, critical sample size, and the graphical representations of self-assessment data. We show that graphical conventions common in the self-assessment literature introduce artifacts that invite misinterpretation. Troublesome conventions include: (y minus x) vs. (x) scatterplots; (y minus x) vs. (x) column graphs aggregated as quantiles; line …