کاربران و پژوهشگران راجع به سیاست های مرتبط با رسانه های اجتماعی چه می گویند؟ (ترسیم نقشه با استفاده از داده های پایگاه های گوگل و اسکوپوس)
آرشیو
چکیده
هدف: عموم کاربران هر روزه به سیاست های مرتبط با رسانه های اجتماعی، از خود حساسیت بیشتری نشان می دهند. این حساسیتِ عموم، تبدیل به حساسیت های پژوهشی نیز شده است و در سال های اخیر، حجم پژوهش هایی که در این رابطه منتشر شده، افزایش یافته است. آگاهی از حساسیت های کاربران به سیاست های رسانه های اجتماعی (با استفاده از تحلیل داده های گوگل ترند) از یک سو و ارتباط آن با جهت گیری هایی که پژوهشگران در خصوص مطالعه این حوزه داشته اند (تحلیل داده های پایگاه اسکوپوس) هدف این پژوهش بوده است. روش: پژوهش حاضر با استفاده از فنون تحلیل شبکه و تحلیل خوشه انجام شده است. دوره زمانی مدنظر برای استخراج داده ها از پایگاه اسکوپوس، سال های ۲۰۰۴ تا ۲۰۲۱ و برای پایگاه گوگل، سال های ۲۰۱۷ تا ۲۰۲۱ بوده است. جست وجو بر اساس رشته عبارت «رسانه های اجتماعی» با ترکیب کلمات کلیدی تنظیم گری، سیاست گذاری و حکمرانی در این دو پایگاه انجام شد. یافته ها: بر اساس رشته عبارت جست وجو شده در پایگاه اسکوپوس، از سال ۲۰۰۴ تا ۲۰۲۱، تعداد ۴۴۶ مقاله یافت شد. شبکه ایجاد شده از تحلیل مقاله ها نشان می دهد که رسانه های اجتماعی، کانون ارتباط در این شبکه قرار گرفته و در طول سال های مختلف، شکل ارتباط شبکه تغییر کرده است. نتایج نشان می دهد که میان مطالعات حوزه سیاست گذاری رسانه های اجتماعی و نتایج جست وجوی کاربران در گوگل، به لحاظ زمانی رابطه نزدیکی وجود دارد. نتیجه گیری: از سال هایی که نگرانی عمومی به عملکرد رسانه های اجتماعی شکل گرفت، شاهد رشد پژوهش های مرتبط با حوزه های سیاستی رسانه های اجتماعی بوده ایم؛ به طوری که در پژوهش ها مفاهیمی مانند حریم خصوصی و محافظت از داده های کاربران رسانه های اجتماعی، در سال های اخیر با تکرار فراوان بررسی شده است.What Do Users and Researchers Say about Social Media Policies? (Mapping data from Google and Scopus)
Objective
These days users show more sensitivity towards the policies related to social media. This public concern has also become a research sensitivity and in recent years, the amount of research published in this regard has increased. Awareness of users' sensitivities towards social media policies (using Google Trend data analysis) on the one hand and its relationship with the orientation that researchers have had regarding the study of this field (Scopus database data analysis) is the aim of this research.
Research Methodology
The present research was conducted using network analysis and cluster analysis techniques. The desired period for extracting data from the Scopus database was from 2004 to 2021 and for the Google database from 2017 to 2021. The search was done based on the keyword of social media by combining the keywords of regulation, policy and governance in these two databases.
Findings
The network created from the analysis of articles related to the searched keywords shows that social media is the center of communication in this network and the form of network communication has changed over the years. The results show that there is a close relationship between social media policy studies and user search results in Google, in terms of time. Since the years when public concern about the performance of social media has been formed, we have witnessed the growth of research related to the policy areas of social media, so concepts such as privacy and data protection of social media users in recent years with It has been discussed many times in researches. The systematic analysis revealed that policy development has received less attention in the literature, while previous studies focused on the development of social media itself. The networks developed for investigating the keywords of the Social Media Policy (SMP) dataset show that privacy, public policy, online networking, and decision-making are the main concerns in the literature. At the same time, the search within Google shows that the public interest in searching relevant keywords has increased over the years but has had a slight decrease in recent years.
Discussion & Conclusion
The analysis shows that the SMP literature is direct to the application of machine learning, policy responses to new challenges, Covid-19, and health care in recent years. These directions tend to be extended as emerging themes in the literature. Machine learning (ML) is used for different purposes in the field of social media. For example, recent studies have developed ML algorithms for detecting bots on different platforms, and intentions to use social media. Some other studies focused on all these emerging themes at the same time. Some of them analyze and monitor the pandemic changes due to Covid-19 applying ML on social media data. ML is increasingly being applied to datasets originated by social media for health purposes such as anxiety, depression, abuse and ... analysis. This article has two levels of innovation. First, the subject of this research, social media policymaking, has been a very important topic in recent years, and this research has tried to conduct a systematic review of it and map this scientific field to help develop future research. Second, this research, like the previous works, did not focus only on presenting a scientific map of a field using the data of scientific databases but also considered the comparison of trends in Scopus and Google search databases. Examining a scientific field about which there are many challenges in the general society is not possible only by examining the previous research of that field. Social media policy-making has been a challenging issue in these years, as it is involved with the public interests of a wide range of citizens and has wide-ranging effects on users' activities, which has confronted policymakers with new issues. Therefore, identifying the issues that are considered by general users of social media and comparing what has been at the center of attention for researchers can be a guide for policymakers in this field. This innovation in the way of dealing with social media policy, which has not been done so far, can be a good example for implementation in other fields of science.
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