مقاله انگلیسی رایگان در مورد کلان داده های شبکه های اجتماعی – الزویر ۲۰۱۸

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مشخصات مقاله
انتشار مقاله سال ۲۰۱۸
تعداد صفحات مقاله انگلیسی ۳ صفحه
هزینه دانلود مقاله انگلیسی رایگان میباشد.
منتشر شده در نشریه الزویر
نوع مقاله ISI
عنوان انگلیسی مقاله Social networking big data: Opportunities, solutions, and challenges
ترجمه عنوان مقاله کلان داده های شبکه های اجتماعی: فرصت ها، راه حل ها و چالش ها
فرمت مقاله انگلیسی  PDF
رشته های مرتبط مهندسی کامپیوتر، فناوری اطلاعات
گرایش های مرتبط امنیت اطلاعات، مدیریت سیستم های اطلاعات، اینترنت و شبکه های گسترده
مجله سل آینده سیستم های کامپیوتری – Future Generation Computer Systems
دانشگاه  Guangdong University of Foreign Studies – China
کلمات کلیدی کلان داده های شبکه های اجتماعی، امنیت، اعتماد، حریم خصوصی، تحلیل شبکه اجتماعی
کلمات کلیدی انگلیسی Social networking big data, Security, Trust, Privacy, Social network analysis
شناسه دیجیتال – doi https://doi.org/10.1016/j.future.2018.05.040
کد محصول E8257
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۱٫ Introduction

Social networking big data [1] is a collection of very huge data sets with a great diversity of types from social networks (e.g., Facebook, WeChat). The emerging paradigm of social networking and big data provide enormous novel approaches to efficiently adopt advanced networking communications and big data analytic schemas by using the existing mechanism. The rapid development of social networking big data brings revolutionary changes to our daily lives and global business, which has been addressed by recent research. However, attackers are taking advantages of social networks to achieve their malicious goals, making the security issue a critical concern when we use social networking big data in practice. There are two important aspects of social networking big data due to the complexity and diversity. One is how to conduct social network analysis based on big data; the other is how to use big data analytic technique to ensure security of social networks using various security mechanisms. Current work on social networking big data focuses on information processing, such as data mining and analysis [2,3]. However, security, trust and privacy of social networking big data are remarkably significant for current researchers and practitioners to address and seek efficient methods to different threats. The special issue concentrates on the challenging topic ‘‘Social Networking Big Data’’, and aims to solicit original research papers that discuss foundational theories, new technologies, security, trust and privacy of social networking big data [4]. In fact, social networking big data has become essential components of various distributed services, applications, and systems [5], including viral marketing, influential bloggers finding, information retrieval, online advertising, sentiment analysis or opinion mining, personalized recommendation [6], opinion leader finding, malware propagation containing, etc. In addition, social networking big data focuses on the collection of big data from social networks, big data preprocessing, selection of evaluation metrics, measuring social influence, design of influence maximization algorithm, performance analysis on related algorithm or model [7,8]. The special issue of FGCS is dedicated to the topics of social networking big data: opportunities, solutions, and challenges as follows. • Fundamentals: Modeling on social influence with big data; social influence analysis with big data; modeling on the characteristics and mechanisms of social networks; influence maximization problem with big data; dynamic social influence analysis in large-scale social networks; social influence analysis in heterogeneous social network; casual relationship in large-scale social networks [9,10]. • Technologies: Recommendations and advertising in social networks with big data; influence propagation in large-scale social networks; user behavior analysis with social influence evaluation; methods for distinguishing the positive, negative, and controversy influence; models, methods, and tools for influence propagation; community detection methods with big data; modeling community influence in social networks; impact of social networks on human social behavior; human behavior analysis in social networks with big data; impact of social networks on human social behavior [5,11].

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