Array
(
    [0] => stdClass Object
        (
            [journal] => stdClass Object
                (
                    [id_jnl] => 87
                )

        )

    [1] => stdClass Object
        (
            [section] => stdClass Object
                (
                    [section] => 289
                )

        )

    [2] => stdClass Object
        (
            [title] => Array
                (
                    [0] => The evolution and future directions of altmetrics research in computer science: A scoping review and bibliometric analysis@en
                )

        )

    [3] => stdClass Object
        (
            [abstract] => Array
                (
                    [0] => Objective. The primary objective of this study was to analyze research performance and identify potential future research related to altmetrics in the last decade.
Methodology. The dataset employed in this study was derived from the Scopus database. The PRISMA flow diagram was utilized during the data collection phase. The results of the bibliometric analysis were used to describe research performance and extract future work and directions. The method known as scoping review and bibliometric analysis (ScoRBA) was used to achieve these goals.
Results. The dataset under consideration encompassed a total of 478 titles, derived from a sample of 93 journals. The Scientometrics journal was the primary source of information disseminating various research results in the field of altmetrics, followed by the Journal of Informetrics. Wang X. was an active and consistent contributor to the field of altmetrics, publishing studies related to the subject between 2015 and 2024. The results of the co-occurrence analysis of author keywords yielded three cluster themes from the altmetrics research. A close examination of the extant literature revealed the emergence of three cluster themes related to altmetrics research: (1) measurement and social impact of research, (2) impact of research through traditional and alternative metrics, and (3) the role of artificial intelligence (AI) and social media in impact analysis and dissemination of research. It was evident that the subjects of social impact and machine learning were intricately intertwined, constituting a multifaceted and evolving research domain characterized by dynamic developments and ongoing advancements.
Conclusion. The study concluded that the altmetrics field had reached a stage of maturity, with a shift in focus from exploratory expansion to more in-depth, high-impact studies. In light of these findings, future research should concentrate on expanding data sources, refining tracking methods, and developing more sophisticated AI-driven models that can integrate both traditional and alternative metrics to achieve a truly holistic understanding of research impact.@en
                )

        )

    [4] => stdClass Object
        (
            [author] => Array
                (
                    [0] => Andri Yanto
                    [1] => Adian Fatchur Rochim
                    [2] => Anne Parlina
                    [3] => Heriyanto
                    [4] => Lis Setyowati
                )

        )

    [5] => stdClass Object
        (
            [subject] => Array
                (
                    [0] => Altmetrics@en
                    [1] => Alternative metrics@en
                    [2] => Scoping review@en
                    [3] => Bibliometric analysis@en
                    [4] => Research impact@en
                )

        )

    [6] => stdClass Object
        (
            [source] => stdClass Object
                (
                    [vol] => 6
                    [nr] => 
                    [year] => 2026
                    [theme] => 
                )

        )

    [7] => stdClass Object
        (
            [datePub] => Array
                (
                    [0] => 2025-11-06
                )

        )

    [8] => stdClass Object
        (
            [DOI] => Array
                (
                    [0] => stdClass Object
                        (
                            [type] => DOI
                            [value] => Array
                                (
                                    [0] => 10.47909/ijsmc.260
                                )

                        )

                )

        )

    [9] => stdClass Object
        (
            [http] => Array
                (
                    [0] => stdClass Object
                        (
                            [type] => HTTP
                            [value] => Array
                                (
                                    [0] => https://ijsmc.pro-metrics.org/index.php/i/article/view/260
                                )

                        )

                    [1] => stdClass Object
                        (
                            [type] => HTTP
                            [value] => Array
                                (
                                    [0] => https://ijsmc.pro-metrics.org/index.php/i/article/view/260/188
                                )

                        )

                )

        )

    [10] => stdClass Object
        (
            [language] => Array
                (
                    [0] => en
                )

        )

    [11] => stdClass Object
        (
            [license] => Array
                (
                    [0] => Copr
                    [1] => by-nc/4.0
                )

        )

)