Machine learning‑based mathematical modelling for prediction of social media consumer behavior using big data analytics Kiran Chaudhary 1 , Mansaf Alam 2 , Mabrook S. Al-Rakhami 3* and Abdu Gumaei 3 Introduction Te easy way to promote the product to everyone is through the social media platform. In this paper, predictive analytics is used to fnd consumer behavior on the social media platform. We have proposed a mathematical and machine learning-based predictive model to fnd the consumer behavior towards products on the social media platform. We have validated the model; the description is given in the result and discussion sec- tion. Te highest accuracy on validation of data is 98% and the transition from Interest to Instagram is 99.51%. Abstract Social media is popular in our society right now. People are using social media plat- forms to purchase various products. We collected the data from various social media platforms. We analyzed the data for prediction of the consumer behavior on the social media platform. We considered the consumer data from Facebook, Twitter, Linked In and YouTube, Instagram, and Pinterest, etc. There are diverse and high-speed, high volume data which are coming from social media platform, so we used predictive big data analytics. In this paper, we have used the concept of big data technology to process data and analyze it to predict consumer behavior on social media. We have analyzed consumer behavior on social media platforms based on some parameters and criteria. We analyzed the consumer perception, attitude towards the social media platform. To get good quality of result, we pre-process data using various data pre- processing to detect outlier, noises, error, and duplicate record. We developed math- ematical modeling using machine learning to predict consumer behavior on the social media platform. This model is a predictive model for predicting consumer behavior on the social media platform. 80% of data are used for training purposes and 20% for testing. Keywords: Big data analytics, Predictive, Consumer perception, Social media, Data analytics, Consumer behaviour Open Access © The Author(s) 2021. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativeco mmons.org/licenses/by/4.0/. RESEARCH Chaudhary et al. J Big Data (2021) 8:73 https://doi.org/10.1186/s40537‑021‑00466‑2 *Correspondence: malrakhami@ksu.edu.sa 3 Research Chair of Pervasive and Mobile Computing, Information Systems Department, College of Computer and Information Sciences, King Saud University, Riyadh 11543, Saudi Arabia Full list of author information is available at the end of the article