A Systematic Review of Research Trend Identification using Text Mining Techniques for Anomaly Detection

Abstract

Text mining techniques have emerged as an important tool to detect anomalies and identify trends in research by analysing a large dataset of text. This includes academic papers, social media posts or other unstructured data. This research has conducted a systematic review of the application of text mining techniques in research based on both qualitative and quantitative data. The findings have highlighted the diverse application of text mining in different fields of research starting from science and healthcare to social computing and forest management.