DataPoll: A Tool Facilitating Big Data Research in Social Sciences

IF 4.5 2区计算机科学 Q1 COMPUTER SCIENCE, CYBERNETICS

IEEE Transactions on Computational Social Systems Pub Date : 2024-12-09 DOI:10.1109/TCSS.2024.3506582

Antonis Charalampous;Constantinos Djouvas;Christos Christodoulou

{"title":"DataPoll: A Tool Facilitating Big Data Research in Social Sciences","authors":"Antonis Charalampous;Constantinos Djouvas;Christos Christodoulou","doi":"10.1109/TCSS.2024.3506582","DOIUrl":null,"url":null,"abstract":"The computational analysis of big data has revolutionized social science research, offering unprecedented insights into societal behaviors and trends through digital data from online sources. However, existing tools often face limitations such as technical complexity, single-source dependency, and a narrow range of analytical capabilities, hindering accessibility and effectiveness. This article introduces DataPoll, an end-to-end big data analysis platform designed to democratize computational social science research. DataPoll simplifies data collection, analysis, and visualization, making advanced analytics accessible to researchers of diverse expertise. It supports multisource data integration, innovative analytical features, and interactive dashboards for exploratory and comparative analyses. By fostering collaboration and enabling the integration of new data sources and analysis methods, DataPoll represents a significant advancement in the field. A comprehensive case study on the Ukrainian–Russian conflict demonstrates its capabilities, showcasing how DataPoll can yield actionable insights into complex social phenomena. This tool empowers researchers to harness the potential of big data for impactful and inclusive research.","PeriodicalId":13044,"journal":{"name":"IEEE Transactions on Computational Social Systems","volume":"12 2","pages":"511-524"},"PeriodicalIF":4.5000,"publicationDate":"2024-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Computational Social Systems","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10785527/","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, CYBERNETICS","Score":null,"Total":0}

引用次数: 0

Abstract

The computational analysis of big data has revolutionized social science research, offering unprecedented insights into societal behaviors and trends through digital data from online sources. However, existing tools often face limitations such as technical complexity, single-source dependency, and a narrow range of analytical capabilities, hindering accessibility and effectiveness. This article introduces DataPoll, an end-to-end big data analysis platform designed to democratize computational social science research. DataPoll simplifies data collection, analysis, and visualization, making advanced analytics accessible to researchers of diverse expertise. It supports multisource data integration, innovative analytical features, and interactive dashboards for exploratory and comparative analyses. By fostering collaboration and enabling the integration of new data sources and analysis methods, DataPoll represents a significant advancement in the field. A comprehensive case study on the Ukrainian–Russian conflict demonstrates its capabilities, showcasing how DataPoll can yield actionable insights into complex social phenomena. This tool empowers researchers to harness the potential of big data for impactful and inclusive research.

查看原文本刊更多论文

DataPoll：促进社会科学大数据研究的工具

大数据的计算分析彻底改变了社会科学研究，通过来自在线资源的数字数据，为社会行为和趋势提供了前所未有的见解。然而，现有的工具经常面临诸如技术复杂性、单源依赖性和分析能力范围狭窄等限制，从而阻碍了可访问性和有效性。本文介绍了DataPoll，一个端到端的大数据分析平台，旨在使计算社会科学研究民主化。DataPoll简化了数据收集、分析和可视化，使不同专业知识的研究人员可以进行高级分析。它支持多源数据集成、创新的分析功能以及用于探索性和比较分析的交互式仪表板。通过促进协作和支持新数据源和分析方法的集成，DataPoll代表了该领域的重大进步。对乌克兰-俄罗斯冲突的全面案例研究展示了它的能力，展示了DataPoll如何能够对复杂的社会现象产生可操作的见解。该工具使研究人员能够利用大数据的潜力进行有影响力和包容性的研究。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

IEEE Transactions on Computational Social Systems Social Sciences-Social Sciences (miscellaneous)

CiteScore

10.00

自引率

20.00%

发文量

316

期刊介绍： IEEE Transactions on Computational Social Systems focuses on such topics as modeling, simulation, analysis and understanding of social systems from the quantitative and/or computational perspective. "Systems" include man-man, man-machine and machine-machine organizations and adversarial situations as well as social media structures and their dynamics. More specifically, the proposed transactions publishes articles on modeling the dynamics of social systems, methodologies for incorporating and representing socio-cultural and behavioral aspects in computational modeling, analysis of social system behavior and structure, and paradigms for social systems modeling and simulation. The journal also features articles on social network dynamics, social intelligence and cognition, social systems design and architectures, socio-cultural modeling and representation, and computational behavior modeling, and their applications.