Evaluating Crowd Sourced Information Using Crowd Sourced Metadata

An information handling system comprising:

• one or more processors;
• a memory coupled to at least one of the processors;
• a set of instructions stored in the memory and executed by at least one of the processors to utilize crowd sourced metadata to weigh candidate answers in a question/answer (QA) system, wherein the set of instructions perform actions of:
• receiving a question from a user;
• identifying one or more question keywords and a context in the question using natural language processing (NLP);
• mining a plurality of crowd sourced data sets for crowd sourced information, wherein the mining is based on the identified question keywords and context, and wherein the crowd sourced data sets have stored therein a collective opinion of a crowd of individuals;
• evaluating the mined crowd sourced information based on a social support attribute included in a crowd sourced metadata, wherein the evaluating results in a most likely answer that is scored based on the social support attribute;
• and
• returning the resulting most likely answer to the user.

The information handling system of claim 12 wherein the actions further comprise:

• identifying the crowd metadata associated with the plurality of candidate answers;
• determining a metadata strength of the identified crowd metadata, wherein the metadata strength is based on one or more factors, and wherein at least one of the factors relates to a social support of an opinion;
• and
• scoring the plurality of candidate answers based on an association of the identified crowd metadata to each of the candidate answers.

A computer program product stored in a computer readable storage medium, comprising computer instructions that, when executed by an information handling system, causes the information handling system to utilize crowd sourced metadata to weigh candidate answers in a question/answer (QA) system by performing actions comprising:

• receiving a question from a user;
• identifying one or more question keywords and a context in the question using natural language processing (NLP);
• mining a plurality of crowd sourced data sets for crowd sourced information, wherein the mining is based on the identified question keywords and context, and wherein the crowd sourced data sets have stored therein a collective opinion of a crowd of individuals;
• evaluating the mined crowd sourced information based on a social support attribute included in a crowd sourced metadata, wherein the evaluating results in a most likely answer that is scored based on the social support attribute;
• and
• returning the resulting most likely answer to the user.