Academic literature on the topic 'Research Subject Categories – SOCIAL SCIENCES – Statistics, computer and systems science'

Purpose The purpose of this paper is to measure the degree of interdisciplinary collaboration in Big Data research based on the co-occurrences of subject categories using Stirling’s diversity index and specialization index. Design/methodology/approach Interdisciplinarity was measured utilizing the descriptive statistics of disciplines, network indicators showing relationships between disciplines and within individual disciplines, interdisciplinary communities, Stirling’s diversity index and specialization index, and a strategic diagram revealing the development status and trends of discipline communities. Findings Comprehensively considering all results, the degree of interdisciplinarity of Big Data research is increasing over time, particularly, after 2013. There is a high level of interdisciplinarity in Big Data research involving a large number of disciplines, but it is unbalanced in distribution. The interdisciplinary collaborations are not intensive on the whole; most disciplines are aggregated into a few distinct communities with computer science, business and economics, mathematics, and biotechnology and applied microbiology as the core. Four major discipline communities in Big Data research represent different directions with different development statuses and trends. Community 1, with computer science as the core, is the most mature and central to the whole interdisciplinary network. Accounting for all network indicators, computer science, engineering, business and economics, social sciences, and mathematics are the most important disciplines in Big Data research. Originality/value This study deepens our understanding of the degree and trend of interdisciplinary collaboration in Big Data research through a longitudinal study and quantitative measures based on two indexes. It has practical implications to study and reveal the interdisciplinary phenomenon and characteristics of related developments of a specific research area, or to conduct comparative studies between different research areas.

Passenger road transport plays an important role in the functioning of the state. This thesis can be substantiated by the fact that passenger road transport performs an important social task — the transportation of passengers. Passenger road transport is fully integrated into the transport system of the country and its subjects. The article considers three main types of activities in which passenger road transport is involved. The authors refer the commercial transportation of passengers to the first type, the transportation of passengers for the own needs of the carrier company to the second, and the use of passenger road transport as a means of individual mobility to the third. If we consider these groups from the point of view of the openness of information on them in various databases, then the first type of activity is the most informative, and the second and third are the least informative. Currently, there is no tool for qualitative and quantitative assessment of the impact of passenger road transport on gross regional products (GRP) and their components. This leads to inadequate reactions in the control system, for example in the field of passenger transportation. Increasing the validity of the development of passenger road transport systems by improving the accuracy of assessing its impact on the socio-economic development of regions is an urgent scientific and practical task. The working hypothesis is that passenger road transport is one of the key factors influencing the development of the subjects of the Russian Federation. Finding the relationship between the qualitative and quantitative assessment of the impact of passenger road transport on GRP and their components will create an understandable and informative tool for assessing the socio-economic condition of the subject in particular, and the country as a whole. The work uses methods of system analysis, mathematical statistics, in particular, correlation and regression analysis. When analyzing the data and processing the results, the authors used the discovery of information databases. The aim of the work is to create theoretical prerequisites for an analytical platform for managing the structure of the passenger vehicle fleet in the regions. The scientific novelty of the study lies in the revealed relationship between the number of passenger vehicles and the gross regional products of the constituent entities of the Russian Federation (correlation coefficients from 0.57 to 0.79), as well as parts of gross regional products by industry (correlation coefficients from 0.07 to 0.9). For the first time, an indicator of the number of conditional passenger motor transport units in the region is proposed, which gives an integral assessment of the methods of passenger motor transport correspondence, taking into account the categories and classes of vehicles. The practical significance of the study lies in the creation of a modern tool for managing passenger transportation in the constituent entities of the Russian Federation by improving the process of operating passenger road transport and managing the number, categories and classes of passenger vehicles. Directions for further research are to apply the above methodology to the integrated management of transport systems of the constituent entities of the Russian Federation.

AbstractThe primary goal of this article is to identify the research fronts on the application of data-driven methods in business and economics. For this purpose, the research literature of the business and economic sciences Subject Categories from the Web of Science is mapped using BibExcel and VOSviewer. Since the assignment to subject categories is done at the journal level and since a journal is often assigned to several subject categories in Web of Science, two mappings are performed: one without considering multiple assignments (broad view) and one considering only those (articles from) journals that have been assigned exclusively to the business and economic sciences subject categories and no others (narrow view). A further aim of this article is therefore to identify differences in the two mappings. Surprisingly, engineering sciences play a major role in the broad mapping, in addition to the economic sciences. In the narrow mapping, however, only the following clusters with a clear business-management focus emerge: (i) Data-driven methods in management in general and data-driven supply chain management in particular, (ii) Data-driven operations research analyses with different business administration/management focuses, (iii) Data-driven methods and processes in economics and finance, and (iv) Data-driven methods in Information Systems. One limitation of the narrow mapping is that many relevant documents are not covered since the journals in which they appear are assigned to multiple subject categories in WoS. The paper comes to the conclusion that the multiple assignments of subject categories in Web of Science may lead to massive changes in the results. Adjacent subject areas—in this specific case the application of data-driven methods in engineering and more mathematically oriented contributions in economics (econometrics) are considered in the broad mapping (not excluding subject categories from neighbouring disciplines) and are even over-represented compared to the core areas of business and economics. If a mapping should only consider the core aspects of particular research fields, it is shown in this use case that the exclusion of Web of Science-subject categories that do not belong to the core areas due to multiple assignments (narrow view), may be a valuable alternative. Finally, it depends on the reader to decide which mapping is more beneficial to them.

This article provides a bibliometric study of the sentiment analysis literature based on Web of Science (WoS) until the end of 2016 to evaluate current research trends, quantitatively and qualitatively. We concentrate on the analysis of scientific documents, distribution of subject categories, languages of documents and languages that have been more investigated in sentiment analysis, most prolific and impactful authors and institutions, venues of publications and their geographic distribution, most cited and hot documents, trends of keywords and future works. Our investigations demonstrate that the most frequent subject categories in this field are computer science, engineering, telecommunications, linguistics, operations research and management science, information science and library science, business and economics, automation and control systems, robotics and social sciences. In addition, the most active venue of publication in this field is Lecture Notes in Computer Science ( LNCS). The United States, China and Singapore have the most prolific or impactful institutions. A keyword analysis demonstrates that sentiment analysis is a more accepted term than opinion mining. Twitter is the most used social network for sentiment analysis and Support Vector Machine ( SVM) is the most used classification method. We also present the most cited and hot documents in this field and authors’ suggestions for future works.

Purpose With the recent developments in information technologies, natural language processing (NLP) practices have made tasks in many areas easier and more practical. Nowadays, especially when big data are used in most research, NLP provides fast and easy methods for processing these data. The purpose of this paper is to identify subfields of library and information science (LIS) where NLP can be used and to provide a guide based on bibliometrics and social network analyses for researchers who intend to study this subject. Design/methodology/approach Within the scope of this study, 6,607 publications, including NLP methods published in the field of LIS, are examined and visualized by social network analysis methods. Findings After evaluating the obtained results, the subject categories of publications, frequently used keywords in these publications and the relationships between these words are revealed. Finally, the core journals and articles are classified thematically for researchers working in the field of LIS and planning to apply NLP in their research. Originality/value The results of this paper draw a general framework for LIS field and guides researchers on new techniques that may be useful in the field.

AbstractThe identification of one’s own research strengths is of crucial importance for research administration at universities. In this case study, two different approaches were applied to the University of Vienna. The first relies on funding and rankings information as well as on other esteem indicators. The second is based on a bibliometric analysis of the publication output. We used two alternative clusterings for publications for the bibliometric analysis: Web of Science subject categories and lists of researchers associated with esteem-indicators. Both, esteem-indicators and bibliometric analysis proved to be useful in identifying research strengths, lead to similar results and are meant to be used together to complement each other. We found that the greatest hindrance in the bibliometric approach lies in the inherent limitations of journals-assignment-based classification systems and the considerable time and efforts for more accurate researcher-based publication analyses. Further investigation on this subject, including new and alternative metrics, is needed and will be conducted in the future. However, the preliminary results already demonstrate the benefits of using esteem-factors together with bibliometric analyses for research strengths definition of universities.

PurposeThe purpose of this paper is to examine the structure, patterns and themes of interdisciplinary collaborations in the digital humanities (DH) research through the application of social network analysis and visualization tools.Design/methodology/approachThe sample includes articles containing DH research in the Web of Science Core Collection as of December 2018. First, co-occurrence data representing collaborations among disciplinary were extracted from the subject category. Second, the descriptive statistics, network indicators and interdisciplinary communities were calculated. Third, the research topics of different interdisciplinary collaboration communities based on system keywords, author keywords, title and abstracts were detected.FindingsThe findings reveal that while the scope of disciplines involved in DH research is broad and evolving over time, most interdisciplinary collaborations are concentrated among several disciplines, including computer science, library and information science, linguistics and literature. The study further uncovers some communities based on closely collaborating disciplines and the evolving nature of such interdisciplinary collaboration communities over time. To better understand the close collaboration ties, the study traces and analyzes the research topics and themes of the interdisciplinary communities. Finally, the implications of the findings for DH research are discussed.Originality/valueThis study applied various informetric methods and tools to reveal the collaboration structure, patterns and themes among disciplinaries in DH research.

Purpose – The use of social media and in particular community Question Answering (Q & A) websites by learners has increased significantly in recent years. The vast amounts of data posted on these sites provide an opportunity to investigate the topics under discussion and those receiving most attention. The purpose of this paper is to automatically analyse the content of a popular computer programming Q & A website, StackOverflow (SO), determine the exact topics of posted Q & As, and narrow down their categories to help determine subject difficulties of learners. By doing so, the authors have been able to rank identified topics and categories according to their frequencies, and therefore, mark the most asked about subjects and, hence, identify the most difficult and challenging topics commonly faced by learners of computer programming and software development. Design/methodology/approach – In this work the authors have adopted a heuristic research approach combined with a text mining approach to investigate the topics and categories of Q & A posts on the SO website. Almost 186,000 Q & A posts were analysed and their categories refined using Wikipedia as a crowd-sourced classification system. After identifying and counting the occurrence frequency of all the topics and categories, their semantic relationships were established. This data were then presented as a rich graph which could be visualized using graph visualization software such as Gephi. Findings – Reported results and corresponding discussion has given an indication that the insight gained from the process can be further refined and potentially used by instructors, teachers, and educators to pay more attention to and focus on the commonly occurring topics/subjects when designing their course material, delivery, and teaching methods. Research limitations/implications – The proposed approach limits the scope of the analysis to a subset of Q & As which contain one or more links to Wikipedia. Therefore, developing more sophisticated text mining methods capable of analysing a larger portion of available data would improve the accuracy and generalizability of the results. Originality/value – The application of text mining and data analytics technologies in education has created a new interdisciplinary field of research between the education and information sciences, called Educational Data Mining (EDM). The work presented in this paper falls under this field of research; and it is an early attempt at investigating the practical applications of text mining technologies in the area of computer science (CS) education.

Purpose This study aims to determine the technical requirements for copyright protection of theses and dissertations for proposing a model for applying in Iran’s National System for Theses and Dissertations (INSTD). Design/methodology/approach This study used a mixed research methodology. The grounded theory was used in the qualitative phase, and a researcher-made checklist was applied in the quantitative phase for surveying the status of the INSTD. Research population included INSTD as well as six information specialists and copyright experts. Data were analysed by using open, axial and selective coding. Findings Based on data extracted from the completed checklists, some technical requirements had been provided in the system. The technical requirements that interviewees pointed out included the following two main classes: technical components and technical-software infrastructures, explored in the phase of the grounded theory. The individual categories included access control, copy control, technical-software challenges, protecting standards, hypertext transfer protocol secure, certificate authority, documentation of thesis and dissertation information, the use of digital object identifiers, copy detection systems, thesis and dissertation integrated systems, digital rights management systems and electronic copyright management systems. Research limitations/implications Considering the subject of this study, only the technical aspect was investigated, and other aspects were not included. In addition, electronic theses and dissertation (ETD) providers were not well aware of copyright issues. Practical implications Using the technical requirements with high security is effective in the INSTD to gain the trust of the authors and encourage them to deposit their ETDs. Social implications The increased use of the system encourages the authors to be more innovative in conducting their research. Originality/value Considering the continued violation of copyright in electronic databases, applying technical requirements for copyright protection and regulating users’ access to the information of theses and dissertations are needed in the INSTD.

The purpose of this study was assessed the impact of good governance on social and economic development in Rwanda. The specific objectives: To determine the impact of good governance on social and economic development brought by Rwanda Governance Board; To analyze challenges facing good governance for social and economic development at Rwanda Governance Board and To establish relationship between good governance and social-economic development in Rwanda. This study was designed as a case study of Rwanda Governance Board using the survey method; a case study was described as analysis of the impact of good governance on social and economic development in Rwanda, assuming that the researcher acquired knowledge regarding the subject under review from in-depth exploration of a single case. It was qualitative analysis that involves careful observation of a situation. All the respondents from the population of different sectors to respond to research questionnaires. The researcher used questionnaires to collect data, As far as this study was concerned, the population was comprised by 145 employees, administrators and policy makers from Rwanda Governance Board. To describe target population of a study as the point of focus from which a generalization was made regarding the research findings. Thus, a sample size of 60 respondents as citizens and staffs from three sectors were considered representative of the total population. I used primary and secondary data to get all information needed in this study, the quantitative data was analyzed using descriptive and inferential statistics after running the data collected through the Statistical Package for Social Sciences (SPSS). The first research objective or research question was to determine the impact of good governance on social and economic development brought by Rwanda Governance Board, the findings of the study discovered that good governance has major contributed to the development of the rest of socio-economic sectors in the country. However, the results of the study shows that the whole civil servants’ been taking part the bad governance which led in destruction of social development, but the responsibility of that bad things have taking the government workers. The second research objective or research question where was to analyze challenges facing good governance for social and economic development at Rwanda Governance Board, therefore the findings of the study exposed that there were a lot of consequence of lack or bad governance which caused corruption fraud and embezzlement, on the other hand public lost their confidence of government institutions. Finally the research objective or research question were understand the significance relationship between good governance and social-economic development in Rwanda, the nature an administrative requirement of good governance may be poorly understood both by the top government organizations and the civil servants besides that the general weakness of accountability and luck of transparency are the challenges of good governance in RGB, besides that most of politicians and civil servant and community members admitted the importance of applying the principal of good governance to enhance economic and social development. Firstly, by in a straight line forthcoming legislative body of the influential as well as civil society, should maintain and implement the principles of good governance to eliminate to rebuild and develop for the country and its people. Secondly, civil servants and politicians should change their attitude through driving fuel for bad governance in the country to eradicate to poverty, in order to create employment opportunities. Thirdly, since there is lack of the principles of good governance, government should establish and implement in a quality control systems be done which will assure transparency and efficiency, also to increase economic development must improve the economic mechanism whose focus is to renew mechanisms and policies so as to release radically productive forces, expand domestic and foreign markets in order to get well infrastructures.

Neste relatório descreve-se o processo de desenvolvimento de um sistema informático que proporciona uma interface de simulação e visualização da instrumentação de aeronaves não tripuladas. O resultado do trabalho desenvolvido insere-se no âmbito do projecto DIVA (1). A plataforma informática desenvolvida compreende dois programas distintos: Simulator: Programa que possibilita a leitura e comunicação de dados, de uma aeronave, previamente guardados. A sua função principal é representar para a interface gráfica um dirigível virtual, simulando missões já realizadas. DIVAgui: Interface gráfica que permite a monitorização dos instrumentos de uma aeronave não tripulada. Na instrumentação virtual são apresentados velocímetros, um altímetro, um indicador de direcção e um horizonte artificial. O estado da comunicação da aeronave e dos seus sensores é indicado e a sua localização GPS é representada num mapa. A informação é actualizada e interpretada nas várias componentes da interface gráfica para que seja facilmente compreendida por parte do utilizador. O sistema foi desenvolvido em C++, utilizando a framework Qt. Dada a complexidade e heterogeneidade dos sistemas envolvidas no processo, utilizou-se uma arquitectura padrão para a comunicação entre objectos: o protocolo CORBA. A aplicação implementada foi testada com êxito em monitorização real do DIVA, produzindo bons resultados.

L'obbiettivo primario di questo lavoro e' stato quello di sviluppare uno strumento finalizzato alla raccolta e alla gestione integrata di considerevoli quantita' di dati acquisiti mediante l'esecuzione di differenti tipologie d'indagine. L'opportunita' di mettere in relazione i parametri geofisici con le caratteristiche geo litologiche del sottosuolo ha permesso di focalizzare l'attenzione sullo studio della risposta sismica locale, utilizzando tecniche di sismica passiva sia per ricavare informazioni sul comportamento dinamico del terreno sia per effettuare un'analisi dei processi tettonici recenti ed in oltre far emergere le caratteristiche morfo strutturali dell'area.