PurposeThis paper aims to straighten out the research progress in the field of maker education, summarize the research hotspots and frontiers of maker education at home and abroad and provide path optimization suggestions for the research and development of this field.Design/methodology/approachIn total, 751 pieces of domestic and the foreign maker education research literature from 2014 to 2021 are retrieved and screened, and literature analysis methods such as keyword analysis and clustering map analysis are used to quantitatively analyze the quantity distribution, published journals, core authors, research institutions and subject keywords of the maker education literature.FindingsIt is found that research in this field is still in the development stage, but the pandemic has severely inhibited maker education and related research. Frontiers at home and abroad have begun to pay attention to the impact of humanistic care on maker education. Strengthening the dialog between multidisciplinary theories requires cross-disciplinary research. Regional and cross-field cooperation and fully grasping the actual situation and constraints of the development of maker education are the cornerstones of bold innovation in maker education research.Originality/valueThis paper uses bibliometric analysis to reveal the severe challenges to the development of maker education due to the normalization of the epidemic. By excavating the research hotspots and research frontiers in this field, it fills the gap that the current research in the field of maker education has not yet formed a complete theoretical framework and evaluation system.
The emergence of new online media has promoted the communication of public cultural information, and systematic evaluation of its communication effectiveness has become an increasingly important research topic.This paper aims to enrich and improve the evaluation index system for the effect of public cultural network communication, and provide suggestions for improving the effect of public cultural network communication and constructing a good communication ecology. Based on factors such as propagation force, guiding force and influence, this paper crawled 78,140 pieces multi-source heterogeneous of 9 Altmetrics index data from Sina Weibo, Baidu, Sogou, Bilibili and other platforms, constructs the evaluation index system of public culture network communication effect under the background of new media, quantifies and analyzes the network communication effect of red public culture in Beijing-Tianjin-Hebei. On this basis, the time series evolution of communication effect is modeled and analyzed, and the law of communication is found systematically. The study finds that the communicating effect of red public culture varies significantly and has a large room for improvement overall; the communicating effect improves steadily with seasonal changes, and the communicating effect in summer and autumn is better than the other two seasons; the ARIMA (Autoregressive Integrated Moving Average) (1,1,1) model can better present the dynamic changes of cultural communication system after the first-order difference of the time series data. This article innovatively embeds the Beijing-Tianjin-Hebei red culture in the public cultural construction system and research system, and a comprehensive communication effect evaluation index system is constructed to measure the effect of public culture network communication under the background of new media and analyze its dynamic evolution.
Computational social science, as an emerging interdisciplinary discipline, is a field ushered in by long-term development of traditional social science. It is committed to supplying data thinking, resources, and analytics to study human social behavior and social operation laws to accurately grasp and judge the developing path of the discipline, which is of great significance to promote the innovation and development of social sciences. This study is to conduct a systematic quantitative analysis from a bibliometric perspective, aiming to provide a reference for scholars to explore the paths and changing rules in the field. We use the relevant literature in Web of Science as the dataset. After eliminating journal calls and irrelevant literature, R language and SciMAT tools are used to visualize and analyze the number of articles, keyword clustering, keyword cooccurrence network, and theme evolution, so as to summarize and sort out the paths of computational social science research. The study found that the annual volume of publications has been gradually increasing and will probably remain active in the next few years with high productivity. Subject themes in different periods are diversified, and the evolutionary relationship is found complex as well. Besides, as a cross discipline, scientific knowledge from different fields cross collides and couples with each other in the big data environment, changing the traditional concept of computational social science and forming a new development path. Recently, the emergence of “big data+” has promoted the rise of new subject areas, making the development of new disciplines a reality.
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