Performance measurement (PM) in public sector organizations plays an important role in measuring progress toward achieving organizational goals, improving performance, and transforming the organization to be more efficient and effective in delivering public services. Over the last two decades many public sector organizations have introduced legislations and frameworks to improve the management of performance. However, public sector organizations are not relying on a universal performance measurement system (PMS) and one recipe to measure performance additionally the increase of performance measurement systems complexity led to an increase in the amount of data to be acquired, processed, and analyzed. Over the last few years, a growing interest in employing big data analytics (BDA) use cases emerged in different public sector domains pursuing the opportunities and potentials of big data analytics to handle the increased amount of structured and unstructured data to support decision-making. A Systematics Literature Review (SLR) is carried out with a combination of text mining techniques and Machine Learning algorithm to automate publication classification was introduced to reduce the burden of study selection process and identifying the most relevant publications to the context of this research.