Social dynamics in conferences: analyses of data from the Live Social Semantics application

Popularity and spread of online social networking in recent years has given a great momentum to the study of dynamics and patterns of social interactions. However, these studies have often been confined to the online world, neglecting its interdependencies with the offline world. This is mainly due to the lack of real data that spans across this divide. The Live Social Semantics application is a novel platform that dissolves this divide, by collecting and integrating data about people from (a) their online social networks and tagging activities from popular social networking sites, (b) their publications and co-authorship networks from semantic repositories, and (c) their real-world face-to-face contacts with other attendees collected via a network of wearable active sensors. This paper investigates the data collected by this application during its deployment at three major conferences, where it was used by more than 400 people. Our analyses show the robustness of the patterns of contacts at various conferences, and the influence of various personal properties (e.g. seniority, conference attendance) on social networking patterns

A scientometric analysis and review of fall from height research in construction

Fall from height (FFH) in the construction industry has earned much attention among researchers in recent years. The present review-based study introduced a science mapping approach to evaluate the FFH studies related to the construction industry. This study, through an extensive bibliometric and scientometric assessment, recognized the most active journals, keywords and the nations in the field of FFH studies since 2000. Analysis of the authors’ keywords revealed the emerging research topics in the FFH research community. Recent studies have been discovered to pay more attention to the application of Computer and Information Technology (CIT) tools, particularly building information modelling (BIM) in research related to FFH. Other emerging research areas in the domain of FFH include rule checking, and prevention through design. The findings summarized the mainstream research areas (e.g., safety management program), discussed existing research gaps in FFH domain (e.g., the adaptability of safety management system), and suggests future directions in FFH research. The recommended future directions could contribute to improving safety for the FFH research community by evaluating existing fall prevention programs in different contexts; integrating multiple CIT tools in the entire project lifecycle; designing fall safety courses to workers associated with temporary agents and prototype safety knowledge tool development. The current study was restricted to the FFH literature sample included the journal articles published only in English and in Scopus

Predicting the dynamics of scientific activities: A diffusion-based network analytic methodology

Copyright © 2018 by Association for Information Science and Technology With the rapid explosion of information and the dramatic development of bibliometric techniques in the past decades, it becomes a challenge to comprehensively, extensively, and efficiently understand science maps. Aim-ing to explore in-depth insights from science maps and predict the dynamics of scientific activities, this paper, based on the co-occurrence statistics of terms derived from scientific documents, proposes a diffusion-based network analytic methodology to conduct the prediction study from two aspects: the research interest of scien-tific researchers and the evolutionary directions of scientific topics. A case study on academic articles down-loaded from three leading journals in the field of bibliometrics demonstrates the feasibility of the methodology. The future directions of bibliometrics are identified, such as the application of information technologies to tradi-tional bibliometric data, the interactions between bibliometrics and science, technology, and innovation policy issues, and individual-level bibliometrics. The results also provide recommendations as potential research inter-ests for a set of experts. The proposed method could be a toolkit to conduct forecasting studies for a given technological area or a given discipline, and a recommender system to assist academic researchers in identify-ing potential research interests and extended areas

git2net - Mining Time-Stamped Co-Editing Networks from Large git Repositories

Data from software repositories have become an important foundation for the empirical study of software engineering processes. A recurring theme in the repository mining literature is the inference of developer networks capturing e.g. collaboration, coordination, or communication from the commit history of projects. Most of the studied networks are based on the co-authorship of software artefacts defined at the level of files, modules, or packages. While this approach has led to insights into the social aspects of software development, it neglects detailed information on code changes and code ownership, e.g. which exact lines of code have been authored by which developers, that is contained in the commit log of software projects. Addressing this issue, we introduce git2net, a scalable python software that facilitates the extraction of fine-grained co-editing networks in large git repositories. It uses text mining techniques to analyse the detailed history of textual modifications within files. This information allows us to construct directed, weighted, and time-stamped networks, where a link signifies that one developer has edited a block of source code originally written by another developer. Our tool is applied in case studies of an Open Source and a commercial software project. We argue that it opens up a massive new source of high-resolution data on human collaboration patterns.Comment: MSR 2019, 12 pages, 10 figure

Assessing Code Authorship: The Case of the Linux Kernel

Code authorship is a key information in large-scale open source systems. Among others, it allows maintainers to assess division of work and identify key collaborators. Interestingly, open-source communities lack guidelines on how to manage authorship. This could be mitigated by setting to build an empirical body of knowledge on how authorship-related measures evolve in successful open-source communities. Towards that direction, we perform a case study on the Linux kernel. Our results show that: (a) only a small portion of developers (26 %) makes significant contributions to the code base; (b) the distribution of the number of files per author is highly skewed --- a small group of top authors (3 %) is responsible for hundreds of files, while most authors (75 %) are responsible for at most 11 files; (c) most authors (62 %) have a specialist profile; (d) authors with a high number of co-authorship connections tend to collaborate with others with less connections.Comment: Accepted at 13th International Conference on Open Source Systems (OSS). 12 page

Application of Artificial Intelligence in Cardiology : A Bibliometric Analysis

Peer reviewe

Uncovering Research Trends in Safety Culture in the Global Construction Industry: A Bibliometric Analysis (1995-2020)

Introduction: Safety culture has mainly been used across several safety management literatures to describe the level of safety within workplaces. This paper presents the research landscape and scientific developments on safety culture in the global construction industry. Methods: The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) approach was employed to identify, screen, and analyze the published documents indexed in the Elsevier Scopus database. Next, the research landscape and scientific developments on the topic were examined by bibliometric analysis (BA) through co-authorship, keywords co-occurrence, and citations. Results: Results showed that 738 documents were published and indexed on the topic between 1995 and 2020. The findings showed that articles are the preferred medium, whereas Engineering is the preferred subject theme for published documents on the topic. The journal of Safety Science (published by Elsevier) is the most influential source of publications on the topic. In contrast, Dongping Fang, based at Tsinghua University (China), is the most influential researcher due to the substantial research grants and financial support from the National Natural Science Foundation. Further analysis showed that the most prolific authors on the topic are based in China, Australia, and Indonesia, although the United States has published the most documents. BA also revealed large networks of researchers and co-occurring keywords and the organizations and countries that currently exist, collaborate, and cite each other works on the topic. Conclusion: The findings indicate that safety culture in the global construction industry has undergone significant scientific developments resulting in high research impact mainly due to its role in preserving the health and safety of workers

A model to improve the Evaluation and Selection of Public Contest´s Candidates (Police Officers) based on AI technologies

Dissertation presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Business AnalyticsThe number of candidates applying to Public Contests is increasing compared to the number of Human Resources employees required for selecting them for Police Forces. This work intends to perceive how those Public Institutions can evaluate and select their candidates efficiently during the different phases of the recruitment process, and for achieving this purpose AI approaches will be studied. This paper presents two research questions and introduces a corresponding systematic literature review, focusing on AI technologies, so the reader is able to understand which are most used and more appropriate to be applied to Police Forces as a complementary recruitment strategy of the National Criminal Investigation Police agency of Portugal – Polícia Judiciária. Design Science Research (DSR) was the methodological approach chosen. The suggestion of a theoretical framework is the main contribution of this study in pair with the segmentation of the candidates (future Criminal Inspectors). It also helped to comprehend the most important facts facing Public Institutions regarding the usage of AI technologies, to make decisions about evaluating and selecting candidates. Following the PRISMA methodology guidelines, a systematic literature review and meta-analyses method was adopted to identify how can the usage and exploitation of transparent AI have a positive impact on the recruitment process of a Public Institution, resulting in an analysis of 34 papers published between 2017 and 2021. The AI-based theoretical framework, applicable within the analysis of literature papers, solves the problem of how the Institutions can gain insights about their candidates while profiling them; how to obtain more accurate information from the interview phase; and how to reach a more rigorous assessment of their emotional intelligence providing a better alignment of moral values. This way, this work aims to advise the improvement of the decision making to be taken by a recruiter of a Police Force Institution, turning it into a more automated and evidence-based decision when it comes to recruiting the adequate candidate for the place

Research Collaboration Influence Analysis Using Dynamic Co-authorship and Citation Networks

Collaborative research is increasing in terms of publications, skills, and formal interactions, which certainly makes it the hotspot in both academia and the industrial sector. Knowing the factors and behavior of dynamic collaboration network provides insights that helps in improving the researcher’s profile and coordinator’s productivity of research. Despite rapid developments in the research collaboration process with various outcomes, its validity is still difficult to address. Existing approaches have used bibliometric network analysis with different aspects to understand collaboration patterns that measure the quality of their corresponding relationships. At this point in time, we would like to investigate an efficient method to outline the credibility of findings in publication—author relations. In this research, we propose a new collaboration method to analyze the structure of research articles using four types of graphs for discerning authors’ influence. We apply different combinations of network relationships and bibliometric analysis on the G-index parameter to disclose their interrelated differences. Our model is designed to find the dynamic indicators of co-authored collaboration with an influence on the author’s behavior in terms of change in research area/interest. In the research we investigate the dynamic relations in an academic field using metadata of openly available articles and collaborating international authors in interrelated areas/domains. Based on filtered evidence of relationship networks and their statistical results, the research shows an increment in productivity and better influence over time