Digital Journalism: Theorizing on Present Times

A lot of change is happening in the world of journalism with the arrival of digital technology. The journalist in this changed scenario is expected to explore multimedia options. There is also a paradigm shift with readers and viewers now becoming a part of the news making process. Write-ups’, pictures, and audiovisual content are increasingly being published by the citizen on websites, blogs, video sharing platforms, and social media. While this has been hailed as democratic and down to top approach, there is a question of credibility. Theories of digital media which have influenced digital journalism have talked about immediacy, interactivity, multimodality, convergence, the broader economic and social factors, the formation of separate networks or reformation of existing networks, a virtual shared platform for communication, actor-network and plurality. However, the question of credibility and the spread of fake news online have raised some new questions. This paper will try to analyze the nature of digital journalism, the various theories which have been applied to explain digital journalism and explain why a new approach is needed in the present scenario

Multivariate Pointwise Information-Driven Data Sampling and Visualization

With increasing computing capabilities of modern supercomputers, the size of the data generated from the scientific simulations is growing rapidly. As a result, application scientists need effective data summarization techniques that can reduce large-scale multivariate spatiotemporal data sets while preserving the important data properties so that the reduced data can answer domain-specific queries involving multiple variables with sufficient accuracy. While analyzing complex scientific events, domain experts often analyze and visualize two or more variables together to obtain a better understanding of the characteristics of the data features. Therefore, data summarization techniques are required to analyze multi-variable relationships in detail and then perform data reduction such that the important features involving multiple variables are preserved in the reduced data. To achieve this, in this work, we propose a data sub-sampling algorithm for performing statistical data summarization that leverages pointwise information theoretic measures to quantify the statistical association of data points considering multiple variables and generates a sub-sampled data that preserves the statistical association among multi-variables. Using such reduced sampled data, we show that multivariate feature query and analysis can be done effectively. The efficacy of the proposed multivariate association driven sampling algorithm is presented by applying it on several scientific data sets.Comment: 25 page

Geometry-Driven Detection, Tracking and Visual Analysis of Viscous and Gravitational Fingers

Viscous and gravitational flow instabilities cause a displacement front to break up into finger-like fluids. The detection and evolutionary analysis of these fingering instabilities are critical in multiple scientific disciplines such as fluid mechanics and hydrogeology. However, previous detection methods of the viscous and gravitational fingers are based on density thresholding, which provides limited geometric information of the fingers. The geometric structures of fingers and their evolution are important yet little studied in the literature. In this work, we explore the geometric detection and evolution of the fingers in detail to elucidate the dynamics of the instability. We propose a ridge voxel detection method to guide the extraction of finger cores from three-dimensional (3D) scalar fields. After skeletonizing finger cores into skeletons, we design a spanning tree based approach to capture how fingers branch spatially from the finger skeletons. Finally, we devise a novel geometric-glyph augmented tracking graph to study how the fingers and their branches grow, merge, and split over time. Feedback from earth scientists demonstrates the usefulness of our approach to performing spatio-temporal geometric analyses of fingers.Comment: Published at IEEE Transactions on Visualization and Computer Graphic

Cognitive Evaluation of Examinees by Dynamic Question Set Generation based on Bloom’s Taxonomy

Educational data mining (EDM) is an emerging topic in recent years steered by data mining and machine learning techniques to enhance students’ overall learning experience and academic progress. In recent years EDM techniques are frequently used to improve assessment systems but the evaluation procedure is majorly marks driven. Developing an evaluation system to distinguish candidates, based on their ability to answer cognitively difficult questions is a challenging task. In this study, a unique methodology is proposed to dynamically rank the candidates to develop an outcome-based online examination system that will properly evaluate a candidate’s cognitive competencies. The questions are segmented into different cognitive groups based on classical Bloom’s educational taxonomy. The Jenks Natural Breaks Optimization technique is used here to segment the questions and as a result, distinct question clusters based on different cognitive levels are obtained. Students are evaluated with different questions from these cognitive groups and ranking is done for individual candidates considering both the marks of the questions and his/her ability to solve questions from different difficulty levels

Digital Journalism: Theorizing on Present Times

A lot of change is happening in the world of journalism with the arrival of digital technology. The journalist in this changed scenario is expected to explore multimedia options. There is also a paradigm shift with readers and viewers now becoming a part of the news making process. Write-ups’, pictures, and audiovisual content are increasingly being published by the citizen on websites, blogs, video sharing platforms, and social media. While this has been hailed as democratic and down to top approach, there is a question of credibility. Theories of digital media which have influenced digital journalism have talked about immediacy, interactivity, multimodality, convergence, the broader economic and social factors, the formation of separate networks or reformation of existing networks, a virtual shared platform for communication, actor-network and plurality. However, the question of credibility and the spread of fake news online have raised some new questions. This paper will try to analyze the nature of digital journalism, the various theories which have been applied to explain digital journalism and explain why a new approach is needed in the present scenario