CITATION.cff

cff-version: 1.2.0
preferred-citation:
  title: >-
    Triple A (AAA): a Tool to Analyze Scientific Literature
    Metadata with Complex Network Parameters
  message: >-
    If you use this software, please cite it using the
    metadata from this file.
  type: conference-paper
  authors:
    - given-names: Maryam
      family-names: Jafarpour
      affiliation: >-
        Department of Algorithms and Computation, School of
        Engineering Science, College of Engineering,
        University of Tehran, Tehran, Iran
    - given-names: Ehsan
      family-names: Bitaraf
      affiliation: >-
        Center for Statistics and Information Technology, Iran
        University of Medical Sciences, Tehran, Iran
      orcid: 'https://orcid.org/0000-0002-6588-7349'
    - given-names: Ali
      family-names: Moeini
      orcid: 'https://orcid.org/0000-0002-6408-3525'
      affiliation: >-
        Department of Algorithms and Computation, School of
        Engineering Science, College of Engineering,
        University of Tehran, Tehran, Iran
    - given-names: Azin
      family-names: Nahvijou
      affiliation: >-
        Cancer Research Centre, Cancer Institute, Tehran
        University of Medical Sciences, Tehran, Iran
  year: 2023
  collection-title: "2023 9th International Conference on Web Research (ICWR)"
  collection-doi: 10.1109/ICWR57742.2023
  start: 342
  end: 345
  identifiers:
    - type: doi
      value: 10.1109/ICWR57742.2023.10139229
    - type: url
      value: 'https://ieeexplore.ieee.org/document/10139229'
  repository-code: 'https://github.com/EhsanBitaraf/triple-a'
  abstract: >-
    It is essential to analyze scientific literature when
    conducting review studies (systematic, narrative, etc.).
    Review articles can improve in quality by choosing or
    incorporating papers with high research impact. The
    quality of research has been measured using a variety of
    indicators. These metrics primarily address certain
    characteristics like the citation index. It is impossible
    to study the caliber of research in any field on an
    individual basis. It has to do with connections.
    Therefore, it would be advantageous to create a network of
    research items. In this study, we introduce a novel tool
    for the analysis of metadata in scientific literature. We
    tested our technique on the literature of breast cancer.
    The tool extracted 49,604 papers resulting in 575,894
    nodes and 1,532,328edges. We looked at the topological and
    structural characteristics of the constructed network,
    briefly. However, this tool can be utilized in any other
    domain of interest.
  keywords:
    - Bibliographies
    - Complex Networks
    - Citation Network
    - Graph Analysis
  license: Apache-2.0