Abstract
Text visualization is concerned with the representation of text in a graphical form to facilitate comprehension of large textual data. Its aim is to improve the ability to understand and utilize the wealth of text-based information available. An essential task in any scientific research is the study and review of previous works in the specified domain, a process that is referred to as the literature survey process. This process involves the identification of prior work and evaluating its relevance to the research question. With the enormous number of published studies available online in digital form, this becomes a cumbersome task for the researcher. This paper presents the design and implementation of a tool that aims to facilitate this process by identifying relevant work and suggesting clusters of articles by conceptual modeling, thus providing different options that enable the researcher to visualize a large number of articles in a graphical easy-to-analyze form. The tool helps the researcher in analyzing and synthesizing the literature and building a conceptual understanding of the designated research area. The evaluation of the tool shows that researchers have found it useful and that it supported the process of relevant work analysis given a specific research question, and 70% of the evaluators of the tool found it very useful.