  Data Visualization has become an important aspect of big data analytics and
has grown in sophistication and variety. We specifically identify the need for
an analytical framework for data visualization with textual information. Data
visualization is a powerful mechanism to represent data, but the usage of
specific graphical representations needs to be better understood and classified
to validate appropriate representation in the contexts of textual data and
avoid distorted depictions of underlying textual data. We identify prominent
textual data visualization approaches and discuss their characteristics. We
discuss the use of multiple graph types in textual data visualization,
including the use of quantity, sense, trend and context textual data
visualization. We create an explanatory classification framework to position
textual data visualization in a unique way so as to provide insights and assist
in appropriate method or graphical representation classification.
