Sentiment analysis of social media data: Business insights and consumer behavior trends in the USA - Montaser, Md Abdullah Al; Ghosh, Bishnu Padh; Barua, Ayan; Karim, Fazle; Das, Bimol Chandra; Shawon, Reza E Rabbi; Chowdhury, Muhammad Shoyaibur Rahman (Edelweiss Applied Science and Technology, 2025)
The digital age has reformed how organizations in the USA reach out to their consumers and has opened up more avenues for understanding consumer sentiment and behavior. This research explored consumer sentiment and behavior trends through social media data with particular emphasis on platforms popular in the USA. By analyzing various social media channels, the study aimed to determine leading trends that drive consumer perception and behavior in real-time. The present research focused on the main social media platforms used in the USA: X-Twitter, Facebook, Instagram, and TikTok. Sentiment analysis data was gathered using the usage of different social media platforms for their unique features and APIs. X-Twitter, being the most useful social media platform for real-time microblogging, provided a very strong API for the analyst to access the tweets, user profiles, and engagement metrics, which is very good for gathering public sentiment and trending topics. With the high volume of users, Facebook exposed the Graph API, which allowed fetching user interactions, comments, and reactions on public posts, giving insight into consumer opinions and brand perception. Also, Instagram's API enabled the collection of visual content along with captions and engagement data, enriching the analysis with multimodal sentiment insights. Three machine learning models were used, most notably, logistic regression, random forest classifier, and XG-Boost. Strategic metrics were used to evaluate the performance of the model: accuracy, precision, recall, and F1-score. With a perfect score for the two algorithms, XG-Boost and Logistic Regression were perfectly able to classify on all metrics, while Random Forest Classifier had high scores close to the other two models, though a little lower in some metrics than the other two. The results of sentiment analysis will provide actionable insights for businesses that want to improve their positioning in the market. By interpreting the data on sentiment, companies in the USA can identify strengths and weaknesses in their offerings and make targeted improvements. Sentiment analysis has proved a crucial tool for US businesses in further improving marketing and customer engagement. Sentiment analysis will help companies in the USA create a meaningful understanding of the perceptions of the general public about its products and services.