Method and system of identifying and allocating sentiment attribution

A server computing system comprising:

• a processor;
• a memory storing a set of instructions, the instructions when executed in the processor causing the processor to implement operations comprising:
• detecting, based at least in part upon a semantic similarity analysis performed in a processor of the computing system, content associated with a plurality of subjects of interest, the content defined in accordance with at least one text character string that is included within social media content data received at the computing system, the content including a sentiment expression associated with the plurality of subjects of interest, the sentiment expression being characterized in accordance with at least one sentiment parameter associated with a sentiment score (NSS);
• identifying, based on continuously monitoring, by the processor, a first and at least a second subjects of interest of the plurality upon accessing, by the processor, a sentiment identification component stored in a memory of the computing system and a sentiment intensity rating associated with the at least one sentiment parameter in accordance with the sentiment expression;
• determining, responsive to identifying the first and at least a second subjects of interest, a first and at least a second portions of the sentiment score that is attributable to the first and the at least a second subjects of interest respectively;
• and
• triggering, based on transmission to a community that receives the social media content data over the distributed computing network, an evidential gathering of facts in rebuttal of the sentiment expression, the evidential gathering being directed to one or more assertions associated with the sentiment expression.

A non-transitory computer readable medium storing instructions, the instructions being executable in a processor, the instructions when executed in the processor causing the processor to implement operations comprising:

• detecting, based at least in part upon a semantic similarity analysis performed in a processor of the computing system, content associated with a plurality of subjects of interest, the content defined in accordance with at least one text character string that is included within social media content data received at the computing system, the content including a sentiment expression associated with the plurality of subjects of interest, the sentiment expression being characterized in accordance with at least one sentiment parameter associated with a sentiment score (NSS);
• identifying, based on continuously monitoring, by the processor, a first and at least a second subjects of interest of the plurality upon accessing, by the processor, a sentiment identification component stored in a memory of the computing system and a sentiment intensity rating associated with the at least one sentiment parameter in accordance with sentiment expression;
• determining, responsive to identifying the first and at least a second subjects of interest, a first and at least a second portions of the sentiment score that is attributable to the first and the at least a second subjects of interest respectively;
• and
• triggering, based on transmission to a community that receives the social media content data over the distributed computing network, an evidential gathering of facts in rebuttal of the sentiment expression, the evidential gathering being directed to one or more assertions associated with the sentiment expression.