Deep Memory Networks for Attitude Identification
Cheng Li, Xiaoxiao Guo, Qiaozhu Mei · 2017
We consider the task of identifying attitudes towards a given set of entities from text. Conventionally, this task is decomposed into two separate subtasks: target detection that identifies whether each entity is mentioned in the text, either explicitly or implicitly, and polarity classification that classifies the exact sentiment towards an identified entity (the target) into positive, negative, or neutral.