Abstract
<p>The purpose of this study was to analyze several brands offering physical and virtual products to determine differences in content marketing, as well as the impact of content cues on brand awareness. An analytical framework examining the relationship between content messaging, cues, and positioning was also developed to investigate social media marketing and brand positioning. The study combines big data techniques, artificial intelligence and machine learning applications, data exploration, disambiguation, and model prediction techniques to observe public behavior and preferences. This study was intended to highlight the importance of functional cues (message recognition) and symbolic cues (positive emotional response) in brand communication, and the findings suggest that brands on social media platforms can use relevant messaging to stimulate brand awareness and facilitate user interaction. In summary, this study contributes to an understanding of key messaging characteristics of branding on social media, explores the differences in user behavior across brands, and documents the impact of cues on user engagement. The results demonstrate that advanced data analysis techniques can be used to extract representative keywords and determine their impact on brand interactions in the context of physical and virtual products. </p> <p>&nbsp;</p>
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