The Use of Artificial Intelligence to Convert Social Media Data into Actionable Insights

The massive volume of social data generated by the extensive adaptation of social media platforms proposes exceptional opportunities to understand opinion trends, customer behavior, and public sentiment. Nonetheless, extracting actionable insights from these complex datasets poses a massive challenge. This research article explores various Artificial Intelligence (AI) methods, such as natural language processing, machine learning, and network analysis, to crack the power of social media data. In time, evidence-based, data-driven information enables us to understand better sentiments, opinions, topics, and trends in digital media culture. The author used a three-step process in this research article: first, existing literature materials were explored using exclusion and inclusion criteria. Second, a survey study was conducted with 200 respondents. Besides, multiple regression analyses for statistical significance were conducted. Lastly, a classroom experiment was conducted with a marketing analytics class with 27 students. Results of the analysis revealed that the combination of independent variables significantly predicted the use of artificial intelligence for converting social media data into actionable insights, F (3, 196) = 67.143, p < .001, accounting for 51% (R2 = .507) of the variance in the use of AI. The variables of NLP (β = −.285, p < .001), machine learning (β = .407, p < .001) and network analysis (β = .275, p < .001) were statistically significant predictors. Findings indicated that using AI to transform social media data into actionable insights carries significant value for businesses, marketing practitioners, and decision-makers.