소셜 미디어에서의 토픽 도출을 활용한 구전 효과와 판매 예측

초록

Purpose This study attempts to predict the automobile sales volume and WoM Effect of electronic cars such as the Tesla Model S. Design/Methodology/Approach This study extracted the data in a new industry, specifically, an electronic car such as the Tesla Model S based on the literature review of the existing media theory: the Media Richness Theory (MRT) and the Media Synchronicity Theory (MST). The unstructured data was used as text data for classifying important topics following the flow of time. Using Latent Dirichlet Allocation (LDA) and Dynamic Topic Modeling (DTM), we deducted the significant topic related to the company performance such as sales volume. Findings We find out that the text mining approach allowed us to identify the derived indicators for an automobile manufacturer’s market success with centrality measures. Also, this research found evidence of conveyance and convergence for the communication process on the web relative to users’ web comments. Research Implications Although previous studies used the economic approach, this study established that social media could capitalize on using conveyance and convergence of the communication process (e.g., conveyance vs. convergence) based on MST through theoretical consideration.

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