Refining the Smart Linkage Across Two Fields: Bridging Latent Topics in Artificial Intelligence and Social Media Marketing

Apparently, distinct fields could possess shared knowledge, and leveraging such shared information could be aiming to implement solutions from one domain into another, enabling greater strategic importance for commercial enterprises. For example, employing solutions from “artificial intelligence” (AI) in designated “social media marketing” (SMM) programs could expedite cross-functional collaboration, potentially leading to a competitive advantage. This area of study is relatively underexplored. In this context, the present research introduces a resilient design model to uncover various linkage possibilities between AI and SMM from a commercial standpoint. Methodologically, the patent database related to AI and SMM is employed to generate latent topics independently, using the classic topic model, Latent Dirichlet allocation. Then, these topics, or implied concepts, are linked through bibliographic coupling. The study’s findings observed cross-concept networks; it reveals a range of concept pairs, and each pair has a unique value of coupling strength. For instance, representative keywords of the top five AI-SMM theme-pairs that show the highest coupling value and offer the maximum commonality of previous work(s) are: [accurate advertising; automation of customer response]; [automation of payment transaction; accuracy; and automation of network database, storage. This study contributes to the literature in three ways. First, each bibliographic coupling-based association shows a unique association of shared knowledge — an influence of common prior art(s). Second, use of citation-based linkage auto-updates to add sustainable features. Third, the patents database is the source of prior art to understand the current state of technology in a particular field. And its latent topics reflect the areas of focus within the broader field. In summary, while the present study maintains a specific focus, its overall analysis is adaptable to other fields, demonstrating its capacity to address intricate challenges in the introduction of automation in information sharing to reduce the knowledge gap. Such smart linkages between two fields may accelerate cross-field communication and foster intelligent cooperation for sustainable industry development by avoiding duplication of efforts.