Objectives The purpose of this study is to explore the activities of industry-academic cooperation programs through text mining analysis. Methods This study analyzed one of the government-supported industry-academic cooperation programs, a LINC project, using web media text materials from blogs, videos, and SNS. Keyword network analysis and CONCOR analysis, which are unstructured data analysis methods, were used to examine what educational activities were performed, what roles they played, and which activities/areas were related together in the LINC project. Results As a result of keyword network analysis, ‘cooperation’, ‘university’, ‘industry’, and ‘business’ were found to be the top frequent keywords, showing the characteristics of LINC project that corporates and universities focus on jointly designing and operating educational programs. The results of keyword centrality analysis showed that ‘education’, ‘university’, ‘company’, and ‘student’ are at the center of the keywords. Analysis by text type showed that the frequency and centrality of keywords differed by the text types, such as blogs, videos, and SNS, respectively. It was inferred that who generated the texts, and what media type were used had an impact on such as result. Conclusions As a result of CONCOR analysis to derive keyword clusters, it was found that activities were mainly performed in four sub-areas: industry/region, education/convergence, field/practice, and competition/promotion. As there were many and strong links between the industry-academic/regional issue and the education/convergence issue, it was inferred that corporate, region, society, and university centered and played major roles of the LINC project. Based on the results, educational implications were suggested.