scholarly journals Data visualization in Indian print media: a comparative study of English and Hindi newspapers

2020 ◽  
Vol 25 (3) ◽  
pp. 554-566
Author(s):  
Amit Kumar ◽  
Poonam Gaur
Keyword(s):  
Comparative Study ◽  
Data Visualization ◽  
News Media ◽  
Data Sets ◽  
Process Data ◽  
Important Place ◽  
Whole Process ◽  
Use Of Data ◽  
Data Journalism ◽  
Data Visualizations

The advancing technology is affecting every aspect of life and journalism is also not untouched by this. Due to digitalization, huge amount of data is being generated and the continuous advancement of computer science has made it possible to extract meaningful information by storing and analysing this huge data. The term “data journalism” has become quite popular over the last decade. Analysing data sets, extracting newsworthy information from it and passing it on to the public is data journalism. Data visualization also has a very important place in this whole process. Data visualization is used to communicate information extracted from the data to the users in a clear, interesting and engaging way. The amount of data-based content has started increasing in the news media as well, so the importance of data visualization has also increased. The use of data visualization improves readers’ reading experience and also helps to better understand the data-based content. This preliminary study focuses on the use of data visualizations by English and Hindi newspapers in India. In this research, a comparative study of various aspects of the use of data visualizations in English and Hindi newspapers has been done. Content analysis with quantitative approach has been employed as the research method. This study reveals that there is a big difference in every aspect of the use of data visualizations in English and Hindi newspapers. English newspaper used data visualizations in a better way than their Hindi counterpart.

scholarly journals Data stories. Rethinking journalistic storytelling in the context of data journalism

2018 ◽  
Vol 18 (1) ◽  
Author(s):  
Wibke Weber ◽  
Martin Engebretsen ◽  
Helen Kennedy
Keyword(s):  
Empirical Study ◽  
Data Visualization ◽  
Narrative Approach ◽  
Use Of Data ◽  
News Organizations ◽  
Data Journalism ◽  
Key Features ◽  
New Form ◽  
Relationship Structure ◽  
Structure And Design

This paper addresses the increased use of data and data visualization in newsrooms, which has yielded a new form of storytelling: data stories. In journalism, data stories or storytelling with data are the new buzzwords. What journalists mean by data stories, however, remains blurred. We use the emergence of data stories as an opportunity to describe the changing understanding of journalistic storytelling. Based on interviews with editorial leaders, data journalists, developers, and designers in 26 major news organizations in Europe, we focus on practitioners’ perspective on data stories. In our empirical study, we identified seven key features of journalistic data stories: data, communicative function, the textual-visual relationship, structure and design of a story, interactivity, and the meta-story. These findings contribute to rethinking the narrative approach to journalism.

scholarly journals Introduction: “Speaking to the Eyes”—Reassessing the Enlightenment in the Digital Age

2021 ◽  
pp. 1-27
Author(s):  
Ileana Baird
Keyword(s):  
Eighteenth Century ◽  
Public Sphere ◽  
Intellectual History ◽  
Data Visualization ◽  
Digital Humanities ◽  
Political Scientist ◽  
Use Of Data ◽  
The Enlightenment ◽  
New Findings ◽  
Data Visualizations

AbstractThis introduction provides a brief survey of the evolution of data visualization from its eighteenth-century beginnings, when the Scottish engineer and political scientist William Playfair created the first statistical graphs, to its present-day developments and use in period-related digital humanities projects. The author highlights the growing use of data visualization in major institutional projects, provides a literature review of representative works that employ data visualizations as a methodological tool, and highlights the contribution that this collection makes to digital humanities and the Enlightenment studies. Addressing essential period-related themes—from issues of canonicity, intellectual history, and book trade practices to canonical authors and texts, gender roles, and public sphere dynamics—, this collection also makes a broader argument about the necessity of expanding the very notion of “Enlightenment” not only spatially but also conceptually, by revisiting its tenets in light of new data. When translating the new findings afforded by the digital in suggestive visualizations, we can unveil unforeseen patterns, trends, connections, or networks of influence that could potentially revise existing master narratives about the period and the ideological structures at the core of the Enlightenment.

Between automation and interpretation : Using data visualization in social media analytics companies

2020 ◽  
Author(s):  
Salla-Maaria Laaksonen ◽  
Juho Pääkkönen
Keyword(s):  
Social Media ◽  
Data Visualization ◽  
Social Media Analytics ◽  
Use Of Data ◽  
Representational Practice ◽  
Field Notes ◽  
Using Data ◽  
Data Visualizations ◽  
Knowledge Claims

This chapter explores the use of data visualizations in social media analytics companies. Drawing on a dataset of ethnographic field notes and thematic interviews in four Finnish social media analytics companies, we argue that data visualizations are crucially involved in how analytics-based knowledge claims become accepted by companies and their clients. Basing on previous research on visualizations in organizations and as a representational practice, we explore their role in social media analytics. We identify three practices of using visualizations, which we have named have simple-boxing, flatter-boxing, and pretty-boxing. We argue that these practices enable analysts to achieve the simultaneous aims of producing credible and valuable analytics in a context marked by high business promises.

scholarly journals Data Visualization Classification Using Simple Convolutional Neural Network Model

2020 ◽  
Vol 11 (1) ◽  
pp. 43-51
Author(s):  
Filip Bajić ◽  
Josip Job ◽  
Krešimir Nenadić
Keyword(s):  
Data Visualization ◽  
Classification Accuracy ◽  
Term Memory ◽  
Average Classification Accuracy ◽  
Use Of Data ◽  
Processing Data ◽  
Level Of Details ◽  
Blind Individuals ◽  
Data Visualizations ◽  
Significant Data

Data visualization is developed from the need to display a vast quantity of information more transparently. Data visualization often incorporates important information that is not listed anywhere in the document and enables the reader to discover significant data and save it in longer-term memory. On the other hand, Internet search engines have difficulty processing data visualization and connecting visualization and the request submitted by the user. With the use of data visualization, all blind individuals and individuals with impaired vision are left out. This article utilizes machine learning to classify data visualizations into 10 classes. Tested model is trained four times on the dataset which is preprocessed through four stages. Achieved accuracy of 89 % is comparable to other methods’ results. It is showed that image processing can impact results, i.e. increasing or decreasing level of details in image impacts on average classification accuracy significantly.

scholarly journals The Use of Data Visualizations for Analyzing Social Trends

2018 ◽  
Vol 1 (1) ◽  
Author(s):  
Richard Schaefer
Keyword(s):  
Data Visualization ◽  
Ethical Dilemmas ◽  
Social Structures ◽  
Social Trends ◽  
Use Of Data ◽  
Visualization Software ◽  
Recent Developments ◽  
Baseline Information ◽  
Data Visualizations

This essay posits that now is a particularly propitious time for the development and use of data visualization as a means for communicating abstract baseline information about society’s complex institutions, organizations, and social structures. It reviews recent developments in off- the-shelf visualization software and describes supporting literature and tutorials. Finally, it presents some of the ethical dilemmas and constraints confronting visualization producers.

scholarly journals Evaluasi Pembangunan Sistem Visualisasi Data (Studi Kasus: Pengelolaan Data pada Kementerian Dalam Negeri Indonesia)

2018 ◽  
Vol 2016 (2) ◽  
Author(s):  
Muhammad Fikry Abyadl ◽  
Sumarno ◽  
Indrianawati
Keyword(s):  
Data Visualization ◽  
Information Visualization ◽  
Suitability Analysis ◽  
Process Data ◽  
Top Down ◽  
Work Unit ◽  
Visualization System ◽  
Basic Task ◽  
And Function ◽  
Data Visualizations

ABSTRAKPembangunan sistem visualisasi data (vista) Kemendagri merupakan langkah awalpengolahan data dan informasi Kemendagri oleh Pusdatinkomtel untuk menyederhanakan, mempermudah, mempercepat, memanipulasi, serta mengolah data dan informasi menjadi berbagai variasi penyajian data. Kebutuhan penyajian data dan informasi pada sistem vista disesuaikan dengan tugas pokok dan fungsi unit kerja di lingkungan Kemendagri. Tujuan penelitian ini adalah untuk mengevaluasi pembangunan sistem vista Kemendagri terkait data, metode, dan implementasi visualisasi data. Metode penelitian yang digunakan adalah metode top-­down, yaitu metode analisis kebutuhan data yang diturunkan berdasarkan tupoksi yang telah terbentuk di instansi tersebut. Hasil identifikasi data berdasarkan tupoksi Kemendagri selanjutnya dibandingkan dengan hasil identifikasi sistem vista Kemendagri sehingga dapat dilakukan analisis kesesuaian data. Dari hasil analisis tersebut, dapat diketahui bahwa sistem vista Kemendagri baru memenuhi 71,11% dari kebutuhan penyajian data dan informasi di lingkungan Kemendagri. Hal tersebut dikarenakan setiap kategori pada sistem vista masih terdapat kekosongan data sehingga belum memenuhi keseluruhan kebutuhan penyajian data.Kata kunci: visualisasi data, sistem visualisasi data, kementerian dalam negeriABSTRACTDevelopment of the Ministry of Home Affair’s data visualization system by Pusdatinkomtel is a first step in processing the Ministry of Home Affair’s data and information. The development aims to simplify, accelerate, facilitate, manipulate and process data and information into various data visualizations. Data and information visualization necessity develops in agreement with basic task and function of work unit in the Ministry of Home Affair’s. This study aims to evaluate development of the Ministry of Home Affair’s data visualization system related to the data, method, and implementation of data visualization. The research method in this study uses a top-­down method. The method analyses data needs based on the basic task and function of work unit in the Ministry of Home Affairs. Furthermore, data suitability analysis is done by comparing result of data identification based on the basic task and function of Ministry of Home Affair’s with data visualization system. The analysis result shows the Ministry of Home Affair’s data visualization system only fulfilling 71.11% from the data and information visualization necessity in the Ministry of Home Affair’s. This is because each category in data visualization system still has data gaps so it has not met the overall needs of data visualization.Keywords: data visualization, data visualization system, ministry of home affairs

Building holistic and agile collection development and assessment

2015 ◽  
Vol 16 (1) ◽  
pp. 62-85 ◽  
Author(s):  
Cheri Jeanette Duncan ◽  
Genya Morgan O'Gara
Keyword(s):  
Quantitative Data ◽  
Holistic Approach ◽  
Assessment Model ◽  
Data Sets ◽  
Collection Development ◽  
Content Type ◽  
Qualitative And Quantitative ◽  
Institutional Goals ◽  
Scholarly Output ◽  
Use Of Data

Purpose – The purpose of this paper is to examine the development of a flexible collections assessment rubric comprised of a suite of tools for more consistently and effectively evaluating and expressing a holistic value of library collections to a variety of constituents, from administrators to faculty and students, with particular emphasis to the use of data already being collected at libraries to “take the temperature” of how responsive collections are in supporting institutional goals. Design/methodology/approach – Using a literature review, internal and external conversations, several collections pilot projects, and a variety of other investigative mechanisms, this paper explores methods for creating a more flexible, holistic collection development and assessment model using both qualitative and quantitative data. Findings – The products of scholarship that academic libraries include in their collections are expanding exponentially and range from journals and monographs in all formats, to databases, data sets, digital text and images, streaming media, visualizations and animations. Content is also being shared in new ways and on a variety of platforms. Yet the framework for evaluating this new landscape of scholarly output is in its infancy. So, how do libraries develop and assess collections in a consistent, holistic, yet agile, manner? Libraries must employ a variety of mechanisms to ensure this goal, while remaining flexible in adapting to the shifting collections environment. Originality/value – In so much as the authors are aware, this is the first paper to examine an agile, holistic approach to collections using both qualitative and quantitative data.

Concept of vayu in ayurved and yogshastra – a comparative study

2019 ◽  
Vol 7 (07) ◽  
Author(s):  
Dr sunila h deo
Keyword(s):  
Comparative Study ◽  
Growth And Development ◽  
Human Life ◽  
Holistic Approach ◽  
The Other ◽  
Eligibility Criteria ◽  
Current Effort ◽  
Important Place ◽  
Body Of Knowledge ◽  
Goals And Objectives

Introduction and Background: Yogashastra and Ayurveda are two ancient Indian sciences that have evolved separately over millennia. Many masters have contributed to the growth and development of these sciences and they have produced seminal literature and body of knowledge in both these streams. The goals and objectives of these two sciences differ from each other and accordingly their approaches too differ from each other.  Both in Yogashastra and Ayurveda, the concept of Vayu has very important place. Current effort is undertaken from the viewpoint to unravel the complementary and contradictory aspects and explore the possibility of combining the concepts so as to evolve the holistic approach. Aim: To compare the concept of Vayu as described in Yogashastra and in Ayurveda. Discussion and Results: Yogashstra the concept of Vayus is aimed solely at attaining mastery over the bodily Vayus by following Yogic disciplines to attain Moksha or final emancipation of the soul from the unending cycle of birth and death. This puts the Yogic discussion of Vayus in the realm of highest spiritual practices with the ultimate conceivable goal of human life that can be taught only by the accomplished masters and eligible seekers who fulfil the strictest eligibility criteria stipulated by Yogic discipline. On the other hand in Ayurveda the concept of Vayus is from the perspective of knowing physiology and causes of various diseases and their treatment by means of various therapies and medicines. All these things are essentially corporeal in nature and do have worldly goals to achieve.

Inside Trending Topic Algorithm: How Do Human Interactions Drive Public Opinion in an Artificial Environment

2021 ◽  
pp. 089443932110415
Author(s):  
Vanessa Russo ◽  
Emiliano del Gobbo
Keyword(s):  
Public Opinion ◽  
Semantic Network ◽  
Opinion Leader ◽  
Computational Techniques ◽  
Data Sets ◽  
Process Data ◽  
Data Set ◽  
Social Actors ◽  
Human Interactions ◽  
Artificial Environment

The object of this research is to exploit the algorithm of Twitter’s trending topic (TT) and identify the elements capable of guiding public opinion in the Italian panorama. The underlying hypotheses that guide the whole article, confirmed by the research results, concern the existence of (a) a limited number of elements at the base of each popular hashtag with very high viral power and (b) hashtags transversal to the themes detected by the Twitter algorithm that define specific opinion polls. Through computational techniques, it was possible to extract and process data sets from six specific hashtags highlighted by TT. In a first step through social network analysis, we analyzed the hashtag semantic network to identify the hashtags transversal to the six TTs. Subsequently, we selected for each data set the contents with high sharing power and created a “potential opinion leader” index to identify users with influencer characteristics. Finally, a cross section of social actors able to guide public opinion in the Twittersphere emerged from the intersection between potentially influential users and the viral contents.

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