ارائه روشی با استفاده از الگوریتم ژنتیک در تشخیص موضع افراد جامعه در رسانه‌های خبری و اجتماعی
محورهای موضوعی : عمومى
مهدی سالخورده حقیقی
1
(دانشکده مهندسی کامپیوتر و فناوری اطلاعات - دانشگاه صنعتی سجاد - مشهد – ايران)
سیدمحمد ابراهیمی
2
(دانشکده مهندسی کامپیوتر و فناوری اطلاعات - دانشگاه صنعتی سجاد - مشهد – ايران)
کلید واژه: رسانه‌های اجتماعی, رسانههاي خبری, تشخیص جوامع, تشخیص موضع افراد,
چکیده مقاله :
گزارش‌های خبری ارائه شده در رسانه‌های اجتماعی و خبری با انواع اسناد و مدارک ارائه می‌شوند و شامل موضوعاتی هستند که جوامع و نظرات مختلف را در برمی‌گیرند. آگاهی از رابطه میان افراد در اسناد می‌تواند به خوانندگان کمک کند تا یک دانش اولیه در‌خصوص موضوع و هدف در اسناد مختلف به‌دست آورند. در این مقاله، روشهای تشخیص جوامع بررسی شده و تکنیکهای مختلف خوشه‌بندی افرادی که نام آن‌ها در مجموعه‌ای از اسناد خبری آورده شده است نیز مورد بررسی قرار میگیرد. این افراد در جوامعی خوشه‌بندی می‌شوند که مواضع مرتبط با یکدیگر دارند. در این مقاله یک روش تشخیص موضع افراد جامعه مبتنی بر یک شبکه دوستی به عنوان مكانيزم پايه معرفی شده و مكانيزم تشخيص جوامع بهبود يافتهاي برمبناي آن ارائه گرديده است. در روش پیشنهادی از ساختار الگوریتم ژنتیک جهت بهبود نرخ تشخیص بهره گرفته شده است. در آزمایش‌ها معیار صحت به منظور مقايسه درنظر گرفته شده است که برای رسیدن به این هدف شاخص رَند نیز استفاده گردیده است. نتایج حاصل از آزمایش‌ها که برمبنای پایگاه‌های داده‌ی واقعی اسناد انتشار یافته در رسانه خبری گوگل نیوز در رابطه با یک موضوع خاص به‌دست‌آمده‌اند، حاکی از کارآمدی و بهره‌وری مطلوب روش پیشنهادی است.
News reports in social media are presented with large volumes of different kinds of documents. The presented topics in these documents focus on different communities and person stances and opinions. Knowing the relationships among persons in the documents can help the readers to obtain a basic knowledge about the subject and the purpose of various documents. In the present paper, we introduce a method for detecting communities that includes the persons with the same stances and ideas. To do this, the persons referenced in different documents are clustered into communities that have related positions and stances. In the presented method. Community-based personalities are identified based on a friendship network as a base method. Then by using a genetic algorithm, the way that these communities are identified is improved. The criterion in the tests is rand index of detection of these communities. The experiments are designed based on real databases that published in Google News on a particular topic. The results indicate the efficiency and desirability of the proposed method
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