Linguistic profiling for digital customization and personalization

A computer program product for linguistic profiling, the computer program product comprising a computer-readable storage medium having program instructions embodied therewith, the program instructions executable by a computer to cause the computer to perform:

• capturing a language input of an individual user;
• analyzing the language input to detect an attribute of the language input by using a machine learning technique based on errors and a gender attribute that is detected by pronoun frequency;
• synthesizing the attribute to characterize a feature of the individual user;
• and
• combining a plurality of synthesized features to create a combined feature profile of the individual user as a one-to-one profile for only the individual user,
• wherein the attribute and the feature are dynamically detected and are not pre-set via the analyzing and synthesizing,
• wherein a crowdsourced approach is utilized for compiling a plurality of new demographic attributes based on a text analysis of the language input of the individual user and the plurality of synthesized features,
• wherein a group view profile is created from a plurality of combined feature profiles aggregated from linked individual users to categorize a group of individuals,
• wherein a media source comprises the group of individuals,
• the method further comprising:
• outputting the combined feature profile to a third-party application;
• outputting the group view profile to a third-party application to generate a report for a group view of the linked individual users;
• and
• identifying a world view within the media source,
• wherein the analyzing includes at least two analysis techniques that work in parallel to each output the attribute with a confidence level to the synthesizing, and
• wherein the synthesizing characterizes the attribute to the feature based on the confidence level.

A linguistic profiling system, said system comprising:

• a processor;
• and
• a memory, the memory storing instructions to cause the processor to perform:
• capturing a language input of an individual user;
• analyzing the language input to detect an attribute of the language input by using a machine learning technique based on errors and a gender attribute that is detected by pronoun frequency;
• synthesizing the attribute to characterize a feature of the individual user;
• and
• combining a plurality of synthesized features to create a combined feature profile of the individual user as a one-to-one profile for only the individual user,
• wherein the attribute and the feature are dynamically detected and are not pre-set via the analyzing and synthesizing,
• wherein a crowdsourced approach is utilized for compiling a plurality of new demographic attributes based on a text analysis of the language input of the individual user and the plurality of synthesized features,
• wherein a group view profile is created from a plurality of combined feature profiles aggregated from linked individual users to categorize a group of individuals,
• wherein a media source comprises the group of individuals,
• the method further comprising:
• outputting the combined feature profile to a third-party application;
• outputting the group view profile to a third-party application to generate a report for a group view of the linked individual users;
• and
• identifying a world view within the media source,
• wherein the analyzing includes at least two analysis techniques that work in parallel to each output the attribute with a confidence level to the synthesizing, and
• wherein the synthesizing characterizes the attribute to the feature based on the confidence level.

A computer-implemented linguistic profiling method, the method comprising:

• capturing a language input of an individual user;
• analyzing the language input to detect an attribute of the language input and profile the language input by using a machine learning technique based on errors and a gender attribute that is detected by pronoun frequency;
• synthesizing the attribute to characterize a feature of the individual user by combining different values for each attribute, based on a confidence level;
• and
• combining a plurality of synthesized features to create a combined feature profile of the individual user as a one-to-one profile for only the individual user, the combined feature profile being a profile of each of the features of the user deducted from the attributes from the language input,
• wherein a group view profile is created from a plurality of combined feature profiles aggregated from linked individual users to categorize a group of individuals,
• wherein the attribute and the feature are dynamically detected and are not pre-set via the analyzing and synthesizing, and
• wherein a crowdsourced approach is utilized for compiling a plurality of new demographic attributes based on a text analysis of the language input of the individual user and the plurality of synthesized features,
• the method further comprising outputting the group view profile to a third-party application to generate a report for a group view of the linked individual users,
• wherein the analyzing includes at least two analysis techniques that work in parallel to each output the attribute with a confidence level to the synthesizing,
• wherein the synthesizing characterizes the attribute to the feature based on the confidence level,
• wherein a media source comprise the group of individuals,
• wherein a world view within the media source is identified.