The popularity of social media has given rise to a vast number of time-stamped logs of tweets, blog posts, text messages, status updates, comments, shares and other communications. These data sets can be explored to identify new types of interactional patterns and trends. Data sonification-converting data into sound-is particularly wellsuited to exploring temporal patterns within time-stamped log data because sound itself is inherently temporal and the human auditory system has excellent temporal resolution. This chapter presents examples of sonifications of social media data, discusses considerations for performing sonification-based analyses, and describes a study in which sonification was used to explore temporal patterns in mobile text message log data. The intent is to allow readers who are unfamiliar with sonification to understand its capabilities and limitations, as well as how they may apply sonification in their own research.