With the rapid development of the Internet and the advent of the digital age, the application of digital intelligent algorithms in the construction of Internet cultural communication platforms is becoming more and more important. Among them, decision tree, as a commonly used machine learning algorithm, plays a key role in this field. This paper aims to discuss the application method and benefits of decision tree in the Internet culture communication platform. This article introduces the background of digital intelligent algorithms in the construction of Internet cultural communication platforms, and discusses its innovations and methods, including content recommendation, data analysis, user portraits, and content review. Through the analysis and learning of user behavior data, digital intelligent algorithms can accurately recommend cultural content of interest to users to achieve personalized services. At the same time, by building a decision tree-based model, user behavior and interests are analyzed and predicted. Utilizing the node and leaf node characteristics of the decision tree, valuable information can be extracted from massive data, helping the platform to accurately push personalized content, improve user experience, and effectively increase the activity and user participation of the Internet cultural communication platform.