Text-based discourse analysis and management

A computer program product comprising one or more computer readable storage media having program instructions collectively stored on the one or more computer readable storage media, the program instructions executable to:

• access a real-time text-based discourse session comprised of multiple text-based posts published by participants, the posts including a question from an author and responses from at least one respondent;
• determine relationships between words in the real-time text-based discourse session utilizing corpus linguistics analysis;
• determine a frequency of the responses of the at least one respondent over time;
• determine an evasiveness score for each of the responses based on natural language processing of the responses, wherein each of the evasiveness scores indicate a level of relevance of a response with respect to the question;
• determine evasiveness rankings for each of the responses based on the determined relationships of words, the frequency of the responses, and the evasiveness scores;
• and
• initiate a change in a display order of the responses based on the evasiveness rankings of the responses.

A system comprising:

• a processor, a computer readable memory, one or more computer readable storage media, and program instructions collectively stored on the one or more computer readable storage media, the program instructions executable to:
• access a real-time text-based discourse session comprised of multiple text-based posts published by participants, the posts including a question from an author and responses from at least one respondent;
• determine relationships between words in the real-time text-based discourse session utilizing corpus linguistics analysis;
• determine a frequency of the responses of the at least one respondent over time;
• determine an evasiveness score for each of the responses based on natural language processing of the responses, wherein each of the evasiveness scores indicate a level of relevance of a response with respect to the question;
• determine a bridged discourse model based on the determined relationships of words, the frequency of the responses, and the evasiveness scores;
• determine evasiveness rankings for each of the responses based on the bridged discourse model;
• determine a display order for the responses based on the evasiveness rankings of the responses;
• and
• when the determined display order is different from a default display order, initiate a change in the display order of the responses from the default display order to a new display order based on the evasiveness rankings of the responses.