The Application of Text Mining and Analytics Studies: A Systematic Literature Review

Abstract

A large amount of textual data is generated everyday through information technology, especially by social media platforms such as social network sites and mobile instant messaging applications. To analyse these large amount of textual data, analysts often turn to techniques called text mining and text analytics. Unfortunately, studies using these techniques are often more occupied with developing a new or extended models rather than determining how the findings could benefit organizations or societies. This occupation with the techniques rather than how the techniques could benefit the organizations or societies at large may render these studies a "plaything for the data scientists" rather than a useful technique to enhance knowledge and improve practice. This study intends to remedy this imbalance by identifying studies that use text mining and analytics techniques to inform organizational and societal practices. To do so, we will employ a method called the systematic literature review (SLR). The technique contains explicit and systematic process that distinguishes it from the conventional literature review. Eventually, the study reveals the source of data of the selected studies, their application area and the parties that will benefit from their findings. Lastly, this study discusses how studies using text mining and analytics can provide benefits to the larger society.