Sentiment analysis has evolved from a lexical classification task into a multidimensional field that seeks to capture the complexity of human communication. While early approaches largely focused on textual content, recent research emphasizes that meaning is often conveyed beyond words, through non-verbal textual elements such as emojis, emoticons, punctuation, capitalization, or deliberate misspellings. These paralinguistic markers play a significant role in shaping the emotional tone of online discourse and consumer-generated content. Neglecting them risks incomplete or misleading interpretations, particularly in contexts where affective nuances drive consumer perceptions and behaviors.

In marketing research, this issue is particularly salient. Online reviews, social media posts, and digital interactions are laden with subtle emotional cues that extend beyond lexical meaning. Ignoring these signals may lead to underestimating or misclassifying consumer attitudes, thereby reducing the accuracy of sentiment-based insights used for managerial decision-making. Emerging tools and models, such as PARA, attempt to systematically incorporate non-verbal textual cues into sentiment analysis, highlighting the growing recognition of their importance.

This chapter underscores the necessity of integrating both verbal and non-verbal markers into sentiment analysis frameworks. By doing so, marketing scholars and practitioners can obtain richer and more reliable insights into consumer emotions, enabling more effective communication strategies, personalized experiences, and improved customer engagement. Future research should continue to explore hybrid approaches that model linguistic and paralinguistic elements together, thus enhancing the explanatory and predictive power of sentiment analysis in digital marketing environments.