Special issue on Social Media Marketing and Financial Forecasting
摘要截稿:
全文截稿: 2019-07-30
影响因子: 4.787
期刊难度:
CCF分类: B类
中科院JCR分区:
• 大类 : 计算机科学 - 1区
• 小类 : 计算机:信息系统 - 1区
• 小类 : 图书情报与档案管理 - 1区
Overview
The last decade has witnessed a huge development in social media interaction. Today, social media is taking over our daily life and becoming ubiquitous. This outburst of social media data has led to an extensive amount of research for analyzing and extracting useful knowledge and workable patterns from social media data. Social media research refers to employing the necessary tools and techniques to monitor the enormous information produced through various social media channels. The research involves aggregating and analyzing socially shared data pertaining to a specific domain or an issue, backed up with supporting study along geopolitical, ethnic, thematic, and psychological dimensions. This analysis provides a useful resource to understand the dynamics of social media interaction and its impact on the world across a large spectrum of areas.
The recent trends in social media research focus mainly on gaining insights of opinions and sentiment on commercial products, financial assets, natural disasters, or sociopolitical events. The research increases our understanding of which government policies are influential, what content has been exchanged across individuals in real-time, and who are the opinion leaders in their local social network.
The huge amount of shared user data (often tagged with timestamps and locations) collected provides subtle aspects of our lifestyle across the globe. It casts light on possible ways to improve people's lives in areas such as education and healthcare. If properly used, social media can be a pillar of the many democracies in the world, by improving transparency and preventing the truth from being hidden.
However, many challenges and difficulties are gradually unveiled along with the revolutionary impacts of social media research. These challenges may fail efforts to marketing and forecasting based on social media analysis. We identify three major challenges here. The first challenge is unbalanced sampling: the voice of the silent majority is overwhelmed by repeated sharing of the same content or Internet water-army activities, which might result in over-representation of data and lead to biased interpretation. Finally, only active social media users are at the focus of the research while a considerable population is being left out. The second challenge lays on dealing with fake content being shared throughout the web for supporting someone’s malicious intent, e.g., fooling the other people or misleading the secondary market. How to introduce the research outcomes about message credibility and cross-validation into real-world applications remains an open problem. While this issue has received a lot of attention because of the disastrous social conditions that it can create. The third challenge is about analyzing social media with minimum data disclosure. Data privacy and security has become a major concern in recent years and repercussions of the European General Data Protection Regulation (GDPR) on social media research are appearing. The Facebook–Cambridge Analytica data scandal also showcased how disastrous it can be when social media data are misused.
Addressing these challenges, especially those of fake content and data privacy and security in the context of social media marketing and financial forecasting will occupy the center stage in social media research in the upcoming years. This will definitely be accompanied by development in the current research areas. The issues of fake content and data security and privacy have got major governments investing a huge amount of money to tackle them and will, at large, be the focus of major developments in the near future. Further, the research space will expand with the development of virtual and augmented reality, which might completely change the nature of data being shared.