A bibliometric analysis of Economic Research-Ekonomska Istrazivanja (2007–2019)

Economic Research-Ekonomska Istrazivanja is an international journal in the research field of business and economics and firstly published in 2007. In this paper, we make a bibliometric analysis of publications in Economic Research-Ekonomska Istrazivanja from 2007 to 2019. According to Web of Science (WoS), we derive 831 publications in the journal after data pre-processing. First, we explore characteristics of publications and citations based on widely recognised bibliometric indicators. Second, we present the influential countries/regions and influential institutions of publications in the journal. Next, we illustrate science mapping analysis according to two visualisation tools that are VOS viewer and CiteSpace. Specifically, co-citation networks and co-authorship networks are conducted to analyse connection of items. We generate bust detection analysis to identify the emerging cited authors and cited journals. Co-occurrence analysis and timeline view analysis of keywords are developed to detect the hot topics and trend of the journal. Finally, we make some discussions about future challenges of the journal in terms of the above analysis. This paper helps in objectively understanding the development of Economic Research-Ekonomska Istrazivanja and provides a valuable reference for the scholars in business and economics

International Collaboration in Science and the Formation of a Core Group

International collaboration as measured by co-authorship relations on refereed papers grew linearly from 1990 to 2005 in terms of the number of papers, but exponentially in terms of the number of international addresses. This confirms Persson et al.'s (2004) hypothesis of an inflation in international collaboration. Patterns in international collaboration in science can be considered as network effects, since there is no political institution mediating relationships at that level except for the initiatives of the European Commission. During the period 2000-2005, the network of global collaborations appears to have reinforced the formation of a core group of fourteen most cooperative countries. This core group can be expected to use knowledge from the global network with great efficiency, since these countries have strong national systems. Countries at the periphery may be disadvantaged by the increased strength of the core

Opinion mining and sentiment analysis in marketing communications: a science mapping analysis in Web of Science (1998–2018)

Opinion mining and sentiment analysis has become ubiquitous in our society, with applications in online searching, computer vision, image understanding, artificial intelligence and marketing communications (MarCom). Within this context, opinion mining and sentiment analysis in marketing communications (OMSAMC) has a strong role in the development of the field by allowing us to understand whether people are satisfied or dissatisfied with our service or product in order to subsequently analyze the strengths and weaknesses of those consumer experiences. To the best of our knowledge, there is no science mapping analysis covering the research about opinion mining and sentiment analysis in the MarCom ecosystem. In this study, we perform a science mapping analysis on the OMSAMC research, in order to provide an overview of the scientific work during the last two decades in this interdisciplinary area and to show trends that could be the basis for future developments in the field. This study was carried out using VOSviewer, CitNetExplorer and InCites based on results from Web of Science (WoS). The results of this analysis show the evolution of the field, by highlighting the most notable authors, institutions, keywords, publications, countries, categories and journals.The research was funded by Programa Operativo FEDER Andalucía 2014‐2020, grant number “La reputación de las organizaciones en una sociedad digital. Elaboración de una Plataforma Inteligente para la Localización, Identificación y Clasificación de Influenciadores en los Medios Sociales Digitales (UMA18‐ FEDERJA‐148)” and The APC was funded by the same research gran

Analysis and visualization of Iranian scientific activities on thalassemia according to scientometric indicators

Background and aim: Today, scientometrics is the main method of assessing and comparing the scientific publications of countries, universities, scientific institutions, specific subjects and authors. The aim of this study was to evaluate the Iranian scientific outputs on thalassemia based on scientometric indicators. Material and methods: In this scientometric study, the social network analysis was used to investigate the co-authorship, word co-occurrence and collaborative coefficient. The study population included 476 articles on thalassemia, indexed in the Web of Science (WoS) from 2006 to 2016. Excel ،Raver-matrix ،SPSS19، UCINET 6/28، Netdraw 2/141 and VOSviewer were utilized for data analysis based on scientometric indicators. Findings: The growth rate (27.94) suggested that scientific outputs on thalassemia had an increasing trend in the WoS. Mean collaborative coefficient was 0.78, and the findings showed that there was a significant relationship between the number of authors and citations to each paper (p=0.05). The Pearson correlation coefficient was 0.650, indicating a direct and positive relationship among the studied variables. However, the co-authorship network of authors and institutes with density of 0.006 and 0.015 indicated low coherence of researchers' network in the field of thalassemia. Conclusion: In the field of thalassemia, both scientific outputs and scientific cooperation level have increasing trend, but compared to other fields, the collaborative network has no good coherence, and it is a great way to achieve the desired status

Visualizing 17 Years of CDIO Influence via Bibliometric Data Analysis

Bibliometric data analysis has gained popularity in recent years as an efficient means of\ua0visualizing multi-dimensional indicators of influence in communities of practice (Youtie &\ua0Shapira, 2008). Such an approach has been used to map emerging fields of research such as\ua0synthetic biology and nanotechnology (Shapira, Kwon, & Youtie, 2017; Youtie & Shapira,\ua02008). Using this approach, one can track citation and social network data over time to develop\ua0a deeper understanding of the influence of the CDIO initiative on engineering education\ua0publications since its inception (i.e., the past 17 years). In this paper, bibliometric data analysis\ua0will be used to examine how publications on the CDIO Initiative have evolved. Visualizations\ua0are presented using an open-source visualization tool, VOSViewer, and used to understand\ua0geographic distribution and co-authorship. A word frequency and co-occurrence analysis has\ua0been used to analyze title and abstract data over the same time period. Geographic author\ua0network analysis reveals continued growth in regional collaborations over the past seventeen\ua0years. Co-authorship by author name reveals a core community of researchers, which has\ua0diverged over time into dispersed collaboration groups. Word co-occurrence analysis of title\ua0and abstract data from Scopus reveals that design-implement and project-based learning\ua0activities have been the central topic of CDIO-related engineering education literature over this\ua0time period. An analysis of the terms “faculty competence” and “learning assessment” indicates\ua0that these topics are comparatively under-served in the literature, representing fertile research\ua0topics for practitioners. The benefit of this research is to provide insight to past development\ua0areas and opportunities for growth in the CDIO Initiative

Visualizing 17 Years of CDIO Influence via Bibliometric Data Analysis

Bibliometric data analysis has gained popularity in recent years as an efficient means of\ua0visualizing multi-dimensional indicators of influence in communities of practice (Youtie &\ua0Shapira, 2008). Such an approach has been used to map emerging fields of research such as\ua0synthetic biology and nanotechnology (Shapira, Kwon, & Youtie, 2017; Youtie & Shapira,\ua02008). Using this approach, one can track citation and social network data over time to develop\ua0a deeper understanding of the influence of the CDIO initiative on engineering education\ua0publications since its inception (i.e., the past 17 years). In this paper, bibliometric data analysis\ua0will be used to examine how publications on the CDIO Initiative have evolved. Visualizations\ua0are presented using an open-source visualization tool, VOSViewer, and used to understand\ua0geographic distribution and co-authorship. A word frequency and co-occurrence analysis has\ua0been used to analyze title and abstract data over the same time period. Geographic author\ua0network analysis reveals continued growth in regional collaborations over the past seventeen\ua0years. Co-authorship by author name reveals a core community of researchers, which has\ua0diverged over time into dispersed collaboration groups. Word co-occurrence analysis of title\ua0and abstract data from Scopus reveals that design-implement and project-based learning\ua0activities have been the central topic of CDIO-related engineering education literature over this\ua0time period. An analysis of the terms “faculty competence” and “learning assessment” indicates\ua0that these topics are comparatively under-served in the literature, representing fertile research\ua0topics for practitioners. The benefit of this research is to provide insight to past development\ua0areas and opportunities for growth in the CDIO Initiative

Reviewing Research Trends:A Scientometric Approach Using Gunshot Residue (GSR) Literature as an Example

The ability to manage, distil and disseminate the significant amount of information that is available from published literature is fast becoming a core and critical skill across all research domains, including that of forensic science. In this study, a simplified scientometric approach has been applied to available literature on gunshot residue (GSR) as a test evidence type aiming to evaluate publication trends and explore the interconnectivity between authors. A total of 731 publications were retrieved using the search engine ‘Scopus’ and come from 1589 known authors, of whom 401 contributed to more than one research output on this subject. Out of the total number of publications, only 35 (4.8%) were found to be Open Access (OA). The Compound Annual Growth Rate (CAGR) for years 2006 and 2016 reveals a much higher growth in publications relating to GSR (8.0%) than the benchmark annual growth rate of 3.9%. The distribution of a broad spectrum of keywords generated from the publications confirms a historical trend, in particular regarding the use of analytical techniques, in the study of gunshot residue. The results inform how relevant information extracted from a bibliometric search can be used to explore, analyse and define new research areas