Social Media Marketing and Financial Forecasting

摘要

The last decade has witnessed a huge development in social media interactions. Today, social media is becoming ubiquitous in two senses: (1) it crosses boundaries and expands to more nations, and (2) it deeply intervenes in our personal life and economic activities. 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 (Hussain & Cambria, 2018). Among those, however, the academic interest in social media marketing and financial forecasting has only increased in recent years (Xing, Cambria, & Welsch, 2018b). For example, only one special issue (Hajli & Laroche, 2019) and two workshops (Chen, Huang, Takamura, & Chen, 2019; Hahn, Hoste, & Tsai, 2018) have been organized on these two topics, respectively. Social media marketing aims to communicate with potential customers to build brand loyalty, attract attention, and increase sales (Cambria, Grassi, Hussain, & Havasi, 2012). As the marketing activities migrate to an online interactive environment, companies can listen-in the customer feedbacks as well as actively influence customer behavior (Constantinides, 2009). Social media-based financial forecasting involves applications such as asset allocation strategies, pricing and valuing financial assets, and stock market prediction (Malandri, Xing, Orsenigo, Vercellis, & Cambria, 2018; Xing, Cambria, & Welsch, 2018a). These applications are not static procedures, to the contrary, they continue to collect information and accordingly revise the output. Both social media marketing and financial forecasting require understanding and leveraging the characteristics of social media data.