Data Warehouse Design to Support Social Media Analysis in a Big Data Environment

Valêncio, Carlos Roberto; Silva, Luis Marcello Moraes; Tenório, William; Zafalon, Geraldo Francisco Donegá; Colombini, Angelo Cesar; Fortes, Márcio Zamboti

doi:10.3844/jcssp.2020.126.136

Cited by 9 publications

(11 citation statements)

References 24 publications

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“…According to the study results, it can be argued that the adjustment and personalization of curricula and courses are possible based on assessments, assignments, and students' interest in further obtaining a specialty. It is possible to model the educational process results depending on the capabilities and resource base of higher education institutions (Sichkarenko, 2018;Valêncio et al, 2020;Williamson, 2016). Furthermore, Big Data can be used to analyze attendance, finding methods to increase student interest in attending institutions.…”

Section: Discussionmentioning

confidence: 99%

Art education on big data and digital platforms base of higher education institutions

Prykhod’ko

Khil

Pobirchenko

et al. 2022

ijhs

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The study aimed to identify Big Data components and the role of the digital platform used for art education. In addition, the aim can be considered a definition of participants' role in the educational process in a broad application of Big Data and digital platforms. In conducting the research, a comprehensive approach was actively used, as well as descriptive methods, qualitative and quantitative ways of monitoring. We used questionnaires to get the necessary information, studied the essential literary sources, collected and analyzed data, and summarized the results. After summarizing the information obtained, it became clear that the Big Data use and digital platforms for art education allowed the transfer of the classical educational process to digital media and created the necessary environment for intellectualizing the educational process. In the future, it is worth considering and searching for options on how to get rid of the gaps in the use of information technology for art education. Relevant issues can be viewed as the problems of security, confidentiality, ethical component, compatibility, data storage, and processing problems, and the acute experienced personnel shortage.

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Section: Discussionmentioning

confidence: 99%

Art education on big data and digital platforms base of higher education institutions

Prykhod’ko

Khil

Pobirchenko

et al. 2022

ijhs

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“…In this context, the analysis of data issued from social media is a promised research topic that has attracted the attention of many researchers and has given birth to novel analysis areas, such as Social Media Analysis. The works related to this area can be subdivided into two major categories: Those designing Data Warehouse (DW) models only from one social media (Twitter, Facebook,…), while others deal with the problem of modeling data warehouse schema from two social media (Moalla et al 2017;Kurnia, P.F 2018;Valêncio et al 2020).…”

Section: Related Workmentioning

confidence: 99%

Building a Data Warehouse for Social Media Analysis: The case of Twitter and Facebook

kraiem,

Feki

2023

Preprint

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“ The proliferation of data generated and stored through social media has experienced a significant surge over the past decade. Consequently, the analysis and interpretation of such data have emerged as valuable sources of insights across diverse contexts, serving as aids for researchers and businesses in making informed decisions. However, the data is widespread, stemming from diverse sources with distinct formats, and is generated at a rapid pace. These characteristics collectively contribute to the intricacy of extracting knowledge from this data, transforming the process into one that is both complex and resource-intensive. The central scientific contribution of this paper lies in the formulation of a social media data integration model, built upon the foundation of a data warehouse. This model is designed to alleviate the computational costs associated with data analysis while concurrently facilitating the application of techniques aimed at discovering meaningful insights. Notably, this study differentiates itself from existing literature by concentrating on both the Facebook and Twitter social media platforms. Additionally, we introduce a model that covers data acquisition, transformation, and loading processes, enabling the extraction of valuable insights even when the data's complexity surpasses human understanding. The results of our study showcase that the proposed data warehouse enhances the effectiveness of data mining algorithms in contrast to related works. Notably, this improvement in quality is achieved while simultaneously reducing execution time.”

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“…University). In addition, individual subjects of the educational process are persons hosting author's materials ((Zillion webinars) (Valêncio et al, 2020), as well as pedagogical workers introducing author's methods and developments into educational school programs. The so-called integrated models are distinguished as a separate approach in Big Data implementation (Bamiah et al, 2018), the content of which is reduced to the integration of classical educational processes with online learning.…”

Section: Literature Reviewmentioning

confidence: 99%

Problems and Prospects for the Art Education Development in Higher Educational Institutions Based on Big Data Technologies and Digital Platforms

Prykhod’ko¹,

Khil²,

Pobirchenko³

et al. 2022

JCT

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In order to build an effective system of providing educational services in the art direction, it is necessary to possess an assessment of the results of Big Data initial implementation. Previously conducted studies on the specifics of implementing digital platforms in the educational art space are incomplete and insufficient. Most universities of different countries introduce these systems independently, and, therefore, there are no methods and principles for implementing such measures in the educational process. The purpose of the present research is to assess the role of Big Data and digital platforms in improving the quality and efficiency of art education. An analysis of assessing the implementation and functioning of digital systems in the leading higher educational institutions of the art direction in Poland, the Czech Republic, and Ukraine was carried out. This made it possible to generalize the experience gained and identify the main trends of this process. This made it possible to generalize the experience gained and identify the main trends of this process. In particular, 70% of students have a positive attitude towards using digital platforms that allow them to expand their awareness and informativeness, and 73% note these platforms as a source of obtaining available information. This made it possible to generalize the experience gained and identify the main tendencies of this process. As a result, modelling of the concept of using Big Data in higher education in the art direction has been presented. The main methods and examples of using Big Data in art education have been defined and characterized. Prospective directions for further application and implementation of innovative digital systems have been indicated. The use of research results creates opportunities for more flexible expansion of existing digital systems and the formation of new directions for subsequent implementation in the educational process. The research pointed to the most significant problem of comprehensive using Big Data by students due to ignorance and lack of awareness of the potential of Big Data in terms of planning, forecasting behavioral actions both in the process of learning, and in future professional activities. Further development of the research topic should focus on the quantitative and qualitative assessment of existing systems and the formation of a detailed methodology for the introduction of the latest educational services in the art education system.

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Data Warehouse Design to Support Social Media Analysis in a Big Data Environment

Abstract: Fortes. This open access article is distributed under a Creative Commons Attribution (CC-BY) 3.0 license.

Cited by 9 publications

References 24 publications

Art education on big data and digital platforms base of higher education institutions

Art education on big data and digital platforms base of higher education institutions

Building a Data Warehouse for Social Media Analysis: The case of Twitter and Facebook

Problems and Prospects for the Art Education Development in Higher Educational Institutions Based on Big Data Technologies and Digital Platforms

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