Navigating computational linguistic in marketing practices: The barriers of natural language processing in social media marketing and a path to future research

Abstract

Social media has emerged as being of pivotal importance for both marketing and analytics due to its unstructured data as a source of rich insights. The increasing adoption of natural language processing (NLP) technologies and solutions has created new marketing opportunities on social media. However, scholars have not devoted sufficient attention to understanding of the barriers and associated challenges of NLP solutions as a social media marketing tool, hindering the full potential of these technologies. The purpose of the paper aims to fill this void in research and practice. We employed a qualitative research approach to identify fourteen challenges and discuss the primary barrier areas: (1) credibility, (2) customization, (3) cross-modality, and (4) convergence. Based on these findings, we initiate a path of future research questions for a deeper understanding of successful adoption of NLP technologies and solutions in marketing practices on social media. Thus, the study advances research in this growing area and fosters future research across different disciplines to improve the practice of marketing in language-rich digital environments.