پارس پروژه پرتال خدمات دانشگاهی
این مقاله علمی پژوهشی (ISI) به زبان انگلیسی از نشریه الزویر مربوط به سال ۲۰۲۲ دارای ۱۵ صفحه انگلیسی با فرمت PDF می باشد در ادامه این صفحه لینک دانلود رایگان مقاله انگلیسی و بخشی از ترجمه فارسی مقاله موجود می باشد.
کد محصول: M1241
سال نشر: ۲۰۲۲
نام ناشر (پایگاه داده): الزویر
نام مجله: Information Processing and Management
نوع مقاله: علمی پژوهشی (Research articles)
تعداد صفحه انگلیسی: ۱۵ صفحه PDF
عنوان کامل فارسی:
مقاله انگلیسی ۲۰۲۲ : آنالیز داده های رسانه های اجتماعی برای سیستم تصمیم گیری تجاری به منظور آنالیز رقابت
عنوان کامل انگلیسی:
Social media data analytics for business decision making system to competitive analysis
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Abstract
For the past few years, business intelligence has been a major field that uses data analysis to produce key information as part of business decision-making. Data collected from social media sites and blogs are analyzed to make business decisions, a process called social media analytics (SMA). This method, which goes beyond ordinary monitoring or a basic analysis of retweets, develops an in-depth insight into the social consumer. After reading the whole report, add the pertinent figures to the table. Add pertinent data from the Brand24 report to the table. During a social media audit, any followers, impressions, engagement, copy/traffic, and brand mentions are key parameters to analyze. For companies and research institutions, the great interest is to analyse and gain knowledge from user-produced data. These data contain useful knowledge, including customer perceptions feedback and product/service suggestions. Due to content saturation, social media’s true meaning regarding business data is hardly ever found. Therefore, in this paper, the business decision making system (BDMS) has been proposed to develop business using social media data analytics. BDMS provides a clear understanding of the key principles, issues and functionality, and big social data developments. Besides, BDMS concentrates on marketing and describes an operational approach for obtaining valuable information from social data. BDMS performs a short and precise description of current use scenarios from the evidence, as per the help of decisions and investment opportunities companies get when using social data analytics. The experimental result shows that BDMS achieves the highest competitive results. With greater accuracy, system dependability, F-1 measurement, and deviation rate of 85.5%, the BDMS system guarantees 93.7%, 86.8%, and 7.0%.
Keywords: Social media audit, Business intelligence, Business decision making, Competitive analysis, Data analytics
۱.Introduction to social media data analytics
In recent times, many businesses are gradually recognizing the engagement of Social Media Networks (SMN) as an external resource for consumer engagement (Chandrasekaran et al., 2021). Since SMN (eg, Facebook, Instagram, and Twitter) connect billions of social media internet users worldwide, organizations face a big database challenge of potentially important user-generated information, generating demand for advanced analytical strategies such as Social Media Data Analytics (SMDA) (Ghani et al., 2019).
A social trade approach attracts customers with transactional interests. Social content and monitoring tactics are intended to deliver relevant information to customers. A sociological approach instead establishes reciprocal consumer ties by integrating social media information into conventional organizational processes. A social networking era changes the interaction between the company and customers, and the aspects which influence consumer commitment need to be identified, which allow customers to engage with each other via social media (Mangold & Faulds, 2009). Castronovo and Huang (2012) propose that social media should be initiated through marketing techniques, including marketing intelligence, promotion, public relations, product management, and customer management…
۶.Conclusions
Business intelligence has been a major field that uses data analysis to produce key information as part of business decision-making. For companies and research institutions, the great interest is to analyse and gain knowledge from user-produced data. In this article, a BDMS has been proposed to develop business using social media data analytics. BDMS provides a clear understanding of the key principles, issues and functionality, and big social data developments. BDMS performs a short precise description of current use scenarios from the evidence, as per the help of decisions and investment opportunities companies get when using social data analytics. The experimental result shows that BDMS achieves the highest competitive results. In the future, this study plans to integrate deep neural networks for social media data analytics. Social media analysis enables data collected from social channels to collect and identify meaning to support business decisions and monitor the performance of activities based on these decisions using social media.