The curious case of posts on Stack Overflow

Community website for programming related Q&A (Question and Answer), Stack Overflow serves as a popular platform to ask questions and respond from other community members. Over the period, user posts on Stack Overflow have turned into a source of valuable information for programmers and the programming industry. By understanding the essential topic of discussions among developers, new insights found about developers' changing trends and needs. This thesis proposes an analysis of user posts on Stack Overflow to find topics of user posts. Distributed topics in the text content of user posts extracted by using the topic modelling technique. Latent Dirichlet allocation (LDA) is applied for topic discovery and extracted the optimal number of topics. The trend of developer interest derived by combining the view count of questions and discovered topics. Based on the analysis within the thesis's scope, developers discuss topics ranging from programming languages, language runtimes, storage, cloud to networking. Scripting programming languages are more discussed compared to non-scripting languages. Discovered topics consist of several recurring categories, i.e., Web Development, Data management and UI development. According to our findings, Machine Learning is gaining popularity as well as data processing and analytics solutions. Mobile development is another favoured subject among developers. The analysis of research findings has inferred that one technology's popularity also reflects in related technology's popularity trend