Twitter is a popular means to disseminate information and currently more than 300 million people are using it actively. Software engineers are no exception; Singer et al. have shown that many developers use Twitter to stay current with recent technological trends. At various time points, many users are posting microblogs (i.e., tweets) about the same topic in Twitter. We refer to this reasonably large set of topically-coherent microblogs in the Twitter space made at a particular point in time as an event. In this work, we perform an exploratory study on software engineering related events in Twitter. We collect a large set of Twitter messages over a period of 8 months that are made by 79,768 Twitter users and filter them by five programming language keywords. We then run a state-of-the-art Twitter event detection algorithm borrowed from the Natural Language Processing (NLP) domain. Next, using the open coding procedure, we manually analyze 1,000 events that are identified by the NLP tool, and create eleven categories of events (10 main categories + “others”). We find that external resource sharing, technical discussion, and software product updates are the “hottest” categories. These findings shed light on hot topics in Twitter that are interesting to many people and they provide guidance to future Twitter analytics studies that develop automated solutions to help users find fresh, relevant, and interesting pieces of information from Twitter stream to keep developers up-to-date with recent trends.