Data analytics system and methods for text data

A computer-readable storage medium, comprising executable instructions that, when executed by a processing system including a processor, facilitate performance of operations, comprising:

• determining a plurality of topics from a plurality of text documents;
• mapping one or more topics in the plurality of topics to each document in the plurality of text documents;
• reducing the plurality of topics into a proper subset of topics based on a frequency of occurrence of each topic in the plurality of text documents;
• identifying n-dimensions of bias for each topic in the proper subset of topics, the n-dimensions of bias identified from text in a corresponding document mapped to the topic;
• creating clusters of topics from the proper subset of topics, wherein each cluster of topics in the clusters of topics is determined from a latent semantic analysis comprising singular value decomposition into orthogonal dimensions, wherein each cluster of topics has an image configuration based on the n-dimensions of bias and the frequency of occurrence for topics in the clusters of topics that distinguishes one cluster from another;
• and
• generating presentable content illustrating each cluster of the clusters of topics according to a corresponding image configuration.

A method, comprising:

• performing, by a system comprising a processor, a latent Dirichlet allocation of a plurality of text documents to determine a plurality of topics;
• creating, by the system, a proper subset of topics from the plurality of topics, based on user input;
• mapping, by the system, one or more topics in the proper subset of topics to each document in the plurality of text documents, thereby creating a plurality of topic-document pairs;
• performing, by the system, a latent semantic analysis of text in the document associated with each topic-document pair to determine n-dimensions of bias for each topic-document pair;
• creating, by the system, clusters of topics from the proper subset of topics, wherein each cluster of topics is determined from a value for each bias dimension of each topic-document pair and a frequency of occurrence of each topic in the plurality of text documents;
• and
• generating, by the system, presentable content that illustrates each cluster of the clusters of topics according to a corresponding image configuration, wherein the image configuration is based on all or a subset of the bias dimensions and the frequency of occurrence of topics in a cluster that distinguishes the cluster from other clusters.