تحلیل کتاب‌سنجی استفاده از هوش مصنوعی در کشف فساد سیاسی و اقتصادی: روندهای فعلی و جهت‌گیری‌های آینده
Translator
Translator
محورهای موضوعی : دو فصلنامه علمی - تخصصی اقتصاد توسعه و برنامه ریزی
رضا رضایی
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سیما اسکندری سبزی
2
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1 -
2 - استادیار دانشگاه آزاد واحد میانه، گروه اقتصاد
کلید واژه: هوش مصنوعی, فساد اقتصادی, فساد سیاسی, تحلیل کتاب‌سنجی,
چکیده مقاله :
علیرغم دامنه گسترده نقش هوش مصنوعی در کشف فسادهای سیاسی و اقتصادی، ادبیات منتشر شده تاکنون، عملکرد فعالیت علمی این حوزه را ارزیابی نکرده است. هدف این تحقیق شناسایی روند و تأثیرگذاری ادبیات منتشر شده در زمینه استفاده از هوش مصنوعی در کشف فساد اقتصادی و سیاسی است. به این منظور داده‌های کتاب‌سنجی 101 سند مرتبط بین سال‌های 2000 تا 2025 از پایگاه داده اسکوپوس استخراج شده است. برای تجزیه و تحلیل از نرم‌افزار VOSviewer نسخه 1.6.20.0 استفاده شد. بر اساس یافته‌ها، حوزه‌های مورد مطالعه را می‌توان در 7 خوشه در نظر گرفت؛ خوشه اول- کشف تقلب و ناهنجاری در رویه‌های عمومی با استفاده از داده‌های باز؛ خوشه دوم- یادگیری ماشین و نقش آن در نظارت بر امور عمومی و اداری ؛ خوشه سوم- جرم، سیاست‌های ضدفساد، و هوش مصنوعی؛ خوشه چهارم- داده‌کاوی در پیش‌بینی و تحلیل در فرایندهای خرید عمومی؛ خوشه پنجم- فساد و پاسخگویی و شفافیت در حاکمیت دولتی؛ خوشه ششم- هوش مصنوعی در قراردادها و رویه‌ها و خوشه هفتم: تکنیک‌های یادگیری عمیق در تحلیل فساد. این تحقیق از طریق به‌کارگیری تحلیل کتاب‌سنجی، ضمن شناسایی مقالات و نویسندگان برجسته، ارتباطات همکاری بین رشته‌ای و روندهای نوظهور در این حوزه را نیز آشکار ساخته است.
Despite the wide scope of the role of artificial intelligence in detecting political and economic corruption, the published literature has not evaluated the performance of scientific activity in this field. The aim of this research is to identify the trend and impact of the published literature on the use of artificial intelligence in detecting economic and political corruption. For this purpose, bibliometric data of 101 relevant documents between 2000 and 2025 were extracted from the Scopus database. VOSviewer version 1.6.20.0 software was used for analysis. Based on the findings, the areas of study can be considered in 7 clusters; Cluster 1 - Detecting fraud and irregularities in public procedures using open data; Cluster 2 - Machine learning and its role in monitoring public and administrative affairs; Cluster 3 - Crime, anti-corruption policies, and artificial intelligence; Cluster 4 - Data mining in prediction and analysis in public procurement processes; Cluster 5 - Corruption and accountability and transparency in government governance; Cluster 6: Artificial Intelligence in Contracts and Procedures and Cluster 7: Deep Learning Techniques in Corruption Analysis. This research, by using bibliometric analysis, has identified prominent articles and authors, as well as revealed interdisciplinary collaborations and emerging trends in this field
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