AI in sentiment analysis can segment

[kexej28769@nongnue]

According to a study by ScienceDirect , artificial neural networks, i.e. machine learning algorithms that AI uses for analysis, achieve more than 85% accuracy in identifying user sentiment. Understanding the context: AI applied to sentiment analysis advances in understanding context, discerning between sarcasm, humor or seriousness in online conversations. This is vital to avoid common misinterpretations in social media listening , such as confusing a sarcastic comment for a positive one . Analysis of emotional trends over time: AI- powered social media listening allows you to track how emotions towards a topic or brand change over time, identifying patterns and anticipating potential shifts in public perception.


This is especially useful for brands during the hong kong whatsapp number data launch of new products or campaigns, allowing them to adjust their strategies based on the public’s emotional response. Emotional audience segmentation: audiences based on their emotional responses, allowing brands to target specific subgroups with more personalized messages. For example, a cosmetics brand could identify and focus on users who express happiness and satisfaction with certain products, strengthening their loyalty with targeted campaigns . Integration with demographic and behavioral data: By combining sentiment analysis with demographic and behavioral data, AI- powered social media listening offers a complete view of the consumer.