Abstract
Market globalization have triggered much more severe challenges for corporates than ever before. Thus, how to survive in this highly fluctuating economic atmosphere is an attractive topic for corporate managers, especially when an economy goes into a severe recession. One of the most consensus conclusions is to highly integrate a corporate’s supply chain network, as it can facilitate knowledge circulation, reduce transportation cost, increase market share, and sustain customer loyalty. However, a corporate’s supply chain relations are unapparent and opaque. To solve such an obstacle, this study integrates text mining (TM) and social network analysis (SNA) techniques to exploit the latent relation among corporates from social media news. Sequentially, this study examines its impact on corporate operating performance forecasting. The empirical result shows that the proposed mechanism is a promising alternative for performance forecasting. Public authorities and decision makers can thus consider the potential implications when forming a future policy.
Recommended Citation
Chang, Te-Ming; Hu, Guo Hsin; Hsu, Ming-Fu; and Lin, Keng-Pei, "Integration of Social Media News Mining and Text Mining Techniques to Determine a Corporate’s Competitive Edge" (2017). PACIS 2017 Proceedings. 35.
https://aisel.aisnet.org/pacis2017/35