The modern marketing environment and the digital public opinion ecosystem are evolving in ways that are more complex and dynamic than ever before. As consumer data accumulates exponentially with the development of social media platforms and e-commerce, analyses that only identify fragmentary frequencies or simple network structures are revealing their limitations.

If social network analysis (SNA) shows the structural “network” (How) among data points and the flow of information, sentiment analysis reveals the intimate human “motivation” (Why) that drives or disconnects those links.

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By combining these two methodologies, it becomes possible to identify how certain information spreads, and within what emotional context clusters are formed and crises are triggered.

We will examine four recent research types that integrate sentiment analysis and SNA.

• “Sentiment-based semantic network analysis,” which identifies the structure and meaning of text
• “Sentiment-weighted user relationship analysis,” which quantifies the positive and negative polarity of networks
• “Sentiment propagation and opinion leadership detection,” which traces the mechanisms of public opinion evolution
• And “homophily-based cluster exploration,” which shows how emotions build digital communities

The insights derived from various research cases can serve as useful guidelines for data-driven practical decision-making such as designing the consumer purchase journey, crisis management, and building public opinion monitoring systems.

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