ACE 2.0: A Comprehensive tool for automatic extraction, analysis, and digital profiling of the researchers in Scientific Communities

Abstract

AbstractIn the current digital era, it is remarkably convenient for researchers to share and collaborate on novel scientific ideas. Scientists aim to accomplish these endeavors through closely knitted scientific communities, depending on the domain. Technological advancements and their evolution overtime gave rise to a boom in the emergence of research communities with unique topics and focuses. Due to the enormous number and vastness of scientific communities, it is an intractable task to analyze scientific communities and administer them from a quantitative and qualitative perspective. Existing tools provide a limited and shallow glance into a scientific community. In this paper, we present a comprehensive system for the analysis of scientific communities called ACE 2.0 (Academic Community Explorer 2.0) which employs state-of-the-art models to automatically, efficiently, and smartly extract, and analyze bibliographic data. Moreover, it provides a range of insights from individual researchers to interactions between communities. These insights include different community-level aspects like collaboration patterns, citation patterns, influential persons with different roles, contributions from geographical locations, topics evolution, and many other fine-grained aspects within each scientific community. Our system considers scholarly publications as a primary source of information. However, it also employs several external resources to collect as much data as possible to correctly identify individual researchers and their contributions. Using all the collected data, ACE 2.0 performs an analysis of scientific communities and automatically performs detailed digital profiling of individual researchers. This analysis identifies trends in their citation, collaboration, contributions, popularity, and role in the community. Additionally, ACE 2.0 introduces a new Semantic index for researchers that takes into account both quantitative and qualitative aspects of the citations received by a researcher and quantifies their influence in the community. To conclude, ACE 2.0 enables us to analyze and oversee the scientific communities using trends and information gathered from different sources encompassing multiple aspects. Therefore, this work motivates us to discover endless new perspectives and opens it up to a wide range of applications in other domains. The demo of ACE 2.0 visualization engine is available at https://ace.opendfki.de/.