Social Computing aims to support the tendency of humans to interact with mobile devices. Technology reinforces this interaction by producing appropriate responses that then lead to improved communication between humans and computational devices. Although latest developments in mobile phone technologies have opened the way for a new generation of mobile social applications that allow users to interact and share information, there is still very limited user support information on how to use different applications. This problem either increases the learning curve of the users, thereby adversely affects their overall efficiency. The main purpose of this paper is to analyze factors that affect the learnability of mobile social software. A sample of 361 respondents was selected, with 345 respondents returning feedback. Primary data was collected through the use of questionnaires and interviews targeting mobile social users in Nakuru County Kenya. Three social networks were used, namely, WhatsApp, Facebook and Twitter. Data analysis was done using descriptive statistics. Findings indicate that interface features affect learnability across the three social networks, with learnability of WhatsApp turning out to be higher than that of compared to Facebook and Twitter. Findings also indicate that more than 60% program supports compatibility with other applications while 59.4% of the respondents agreed that maintaining language is cheap across the three social networks. Other findings indicate that WhatsApp’s memorability is easy to execute compared to that of Facebook and Twitter