scholarly journals Big data method and its application in innovation education research

2021 ◽  
Vol 290 ◽  
pp. 03022
Author(s):  
Yankui Song ◽  
Chuijiao Jie ◽  
Zhijin Xu
Keyword(s):  
Big Data ◽  
Social Science ◽  
Timing Analysis ◽  
Social Science Research ◽  
Science Research ◽  
Development Trend ◽  
Scientific Basis ◽  
Source Analysis ◽  
Knowledge Mapping ◽  
Big Data Technology

Big data technology is a new stage of information development. In recent years, it has been widely used in many fields, especially in social science research. This paper analyzes the development status and significance of the combination of big data technology and social science research, on the basis of summarizing and combing the concept of big data and its important role. Taking the application of big data method in the research of innovation education as an example, this paper makes a series of visualization analysis with Citespace software on the related literature with the theme of “big data and innovation education” collected by CNKI, such as annual analysis, literature source analysis, co-occurrence analysis of authors, organization analysis, keyword clustering analysis and keyword timing analysis. This paper also draws the corresponding knowledge mapping, clarifies its research status, hot spots and development trend, and provides scientific basis for the research of innovation education. Thus the paper believes that the research on big data and innovation education needs to strengthen interdisciplinary communication and cooperation, refine and deepen the research theme and content.

scholarly journals The role of administrative data in the big data revolution in social science research

2016 ◽  
Vol 59 ◽  
pp. 1-12 ◽  
Author(s):  
Roxanne Connelly ◽  
Christopher J. Playford ◽  
Vernon Gayle ◽  
Chris Dibben
Keyword(s):  
Big Data ◽  
Social Science ◽  
Administrative Data ◽  
Social Science Research ◽  
Science Research

scholarly journals Environmental Economic Research Has an Audience But Not a Sponsor: Discussion

1994 ◽  
Vol 23 (2) ◽  
pp. 120-124 ◽  
Author(s):  
Mary Jo Kealy
Keyword(s):  
Environmental Economic ◽  
Social Science ◽  
Research Agenda ◽  
Social Science Research ◽  
Science Research ◽  
Scientific Basis ◽  
Federal Agencies ◽  
Environmental Research ◽  
Economic Research ◽  
National Environmental

There exists no mechanism for federal agencies, national laboratories, industry, and academic institutions to set a national environmental research agenda. Moreover, funding for social science research is inadequate for providing a sound scientific basis for making environmental policy. Despite this lack of leadership, it is quite possible to define an environmental economic research agenda that could lead to improved policies for protecting and managing the environment. The present paper makes some recommendations from an insider's viewpoint.

Trade-Offs, Limitations, and Promises of Big Data in Social Science Research

2014 ◽  
Vol 31 (4) ◽  
pp. 331-338 ◽  
Author(s):  
Patricia White ◽  
R. Saylor Breckenridge
Keyword(s):  
Big Data ◽  
Social Science ◽  
Social Science Research ◽  
Science Research ◽  
Trade Offs

Causation, Correlation, and Big Data in Social Science Research

2015 ◽  
Vol 7 (4) ◽  
pp. 447-472 ◽  
Author(s):  
Josh Cowls ◽  
Ralph Schroeder
Keyword(s):  
Big Data ◽  
Social Science ◽  
Social Science Research ◽  
Science Research

Teaching stats: A crisis in Irish sociology?

2015 ◽  
Vol 24 (1) ◽  
pp. 102-111
Author(s):  
Carmel Hannan
Keyword(s):  
Big Data ◽  
Social Science ◽  
Mixed Methods Research ◽  
Quantitative Methods ◽  
Social Science Research ◽  
Science Research ◽  
Undergraduate Level ◽  
Sociology Departments ◽  
The Uk ◽  
Research Councils

There is now a lack of quantitative capacity among practitioners and teachers in sociology in Ireland. Yet interest in the value of quantitative methods among governments, funding organisations and society in general are on the increase. Social science research councils and funders in other countries, notably the UK, have realised there is a problem and are now attempting to remedy this through increased funding for the recruitment of quantitatively trained academics for example, Q-Step. The paper examines a number of developments notably Big Data, increases in transdisciplinary research and developments in mixed methods research which, it is argued, underline the need for more and better quantitative methods teaching in sociology. The paper calls for sociology departments to re-think their curricula and actively promote the teaching of a range of methods at the undergraduate level.

scholarly journals Big Data for Social Science Research

Ubiquity ◽  
2018 ◽  
Vol 2018 (January) ◽  
pp. 1-7 ◽  
Author(s):  
Mark Birkin
Keyword(s):  
Big Data ◽  
Social Science ◽  
Social Science Research ◽  
Science Research

scholarly journals Early social science research about Big Data

2016 ◽  
pp. scw021 ◽  
Author(s):  
Jan Youtie ◽  
Alan L. Porter ◽  
Ying Huang
Keyword(s):  
Big Data ◽  
Social Science ◽  
Social Science Research ◽  
Science Research

scholarly journals Big Data, Data Science and Emerging Analytic tools : Impact in social science

2019 ◽  
Author(s):  
Satabdi Saha ◽  
Tapabrata Maiti
Keyword(s):  
Big Data ◽  
Internet Of Things ◽  
Social Science ◽  
Data Analytics ◽  
Data Science ◽  
Social Science Research ◽  
Big Data Analytics ◽  
Science Research ◽  
Data Sources ◽  
The Internet

Rapid advancement of the Internet and Internet of Things have led to companies generating gigantic volumes of data in every field of business. Big data research has thus become one of the most prominent topic of discussion garnering simultaneous attention from academia and industry. This paper attempts to understand the significance of big data in current scientific research and outline its unique characteristics, otherwise unavailable from traditional data sources. We focus on how big data has altered the scope and dimension of data science thus making it severely interdisciplinary. We further discuss the significance and opportunities of big data in the domain of social science research with a scrutiny of the challenges previously faced while using smaller datasets. Given the extensive utilization of big data analytics in all forms of socio-technical research, we argue the need to critically interrogate its assumptions and biases; thereby advocating the need for creating a just and ethical big data world.

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