Special Issue "Big Data and Social Sciences"

A special issue of Social Sciences (ISSN 2076-0760).

Deadline for manuscript submissions: 15 October 2020.

Special Issue Editors

Dr. Juan Leiva
E-Mail Website
Guest Editor
Research Group in Inclusive Educational Development and Innovation, Faculty of Education Sciences, University of Malaga, Office 7.06. Boulevard Louis Pasteur, 25, Campus of Teatinos, C.P. 29010 Malaga, Spain
Interests: interculturality; inclusive education; teacher training; big data; augmented reality
Special Issues and Collections in MDPI journals
Dr. Antonio Matas
E-Mail Website
Guest Editor
Research Group in Inclusive Educational Development and Innovation, Faculty of Education Sciences, University of Malaga, Office 6.08. Boulevard Louis Pasteur, 25, Campus of Teatinos, C.P. 29010 Malaga, Spain
Interests: big data; educational innovation; measurement; evaluation

Special Issue Information

Dear colleagues,

This special edition aims to discuss the potential of Big Data in different areas of social sciences such as education, social work, social psychology, sociology and citizen science.  The speed and rapidity of technological and scientific changes has involved the possibility of compiling massive data whose social analysis can be enormously beneficial for improving the quality of life of human beings. Massive information analysis is an opportunity for responsible, respectful and operational decision-making.

 It Is extremely interesting to address the multiple dimensions and projective functions of the Big Data as the description, diagnosis, prediction and prescription of social and educational proposals for the improvement of public services and devices and the social initiative. In this sense, it is very interesting to analyze the evolution of the training needs of the population, both young people and adults, as well as the elderly, for the establishment of social, cultural, educational and public health proposals that are sustainable in the framework of a society in permanent change, dynamism and complexity.

We anticipate that this special issue will become a cornerstone of scientific literature for the Big Data in social sciences. We are interested in receiving documents from different social disciplines that illustrate through studies, research and reviews the potential for improvement of the Big Data. We also welcome the contributions outlining the positive and critical aspects of the Big Data for a calm analysis of the role it can play in the coming years. In addition, we are interested in contributions that show the analytical link and the learning and development potential of the Big Data for the implementation of improvements in education, social work, health and other services of general interest to society.

We invite you to contribute to this topic by presenting research papers or exhaustive reviews in various fields of social sciences such as education, psychology, Social work, sociology, among others. The documents selected for this special edition are subject to a rigorous peer review procedure with the aim of rapidly and widely disseminating the results of the research, development and applications of the Big Data in different Areas and contexts of scientific and professional development.

Dr. Juan Leiva
Dr. Antonio Matas
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a double-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Social Sciences is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • big data
  • social sciences
  • learning analysis
  • big data in education
  • big data in social work
  • big data training

Published Papers (2 papers)

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Research

Open AccessArticle
Email Based Institutional Network Analysis: Applications and Risks
Soc. Sci. 2019, 8(11), 306; https://doi.org/10.3390/socsci8110306 (registering DOI) - 08 Nov 2019
Abstract
Social Network Analysis can be applied to describe the patterns of communication within an organisation. We explore how extending standard methods, by accounting for the direction and volume of emails, can reveal information regarding the roles of individual members. We propose an approach [...] Read more.
Social Network Analysis can be applied to describe the patterns of communication within an organisation. We explore how extending standard methods, by accounting for the direction and volume of emails, can reveal information regarding the roles of individual members. We propose an approach that models certain operational aspects of the organization, based on directional and weighted indicators. The approach is transferable to other types of social network with asymmetrical connections among its members. However, its applicability is limited by privacy concerns, the existence of multiple alternative communication channels that evolve over time, the difficulty of establishing clear links between organisational structure and efficiency and, most importantly, the challenge of setting up a system that measures the impact of communication behavior without influencing the communication behaviour itself. Full article
(This article belongs to the Special Issue Big Data and Social Sciences)
Open AccessArticle
Big Data in Education. A Bibliometric Review
Soc. Sci. 2019, 8(8), 223; https://doi.org/10.3390/socsci8080223 - 25 Jul 2019
Cited by 1
Abstract
The handling of a large amount of data to analyze certain behaviors is reaching a great popularity in the decade 2010–2020. This phenomenon has been called Big Data. In the field of education, the analysis of this large amount of data, generated to [...] Read more.
The handling of a large amount of data to analyze certain behaviors is reaching a great popularity in the decade 2010–2020. This phenomenon has been called Big Data. In the field of education, the analysis of this large amount of data, generated to a greater extent by students, has begun to be introduced in order to improve the teaching–learning process. In this paper, it was proposed as an objective to analyze the scientific production on Big Data in education in the databases Web of Science (WOS), Scopus, ERIC, and PsycINFO. A bibliometric study was carried out on a sample of 1491 scientific documents. Among the results, the increase in publications in 2017 and the configuration of certain journals, countries and authors as references in the subject matter stand out. Finally, potential explanations for the study findings and suggestions for future research are discussed. Full article
(This article belongs to the Special Issue Big Data and Social Sciences)
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