Using neural network and score weighing to incorporate contextual data in sentiment analysis

Abstract

An artificial neural network (ANN) determines a conversation snippet sentiment score based on content of the conversation snippet and contextual attributes associated with the conversation snippet. Contextual attributes may include, for example, a role within an organizational hierarchy of a user participating in the conversation snippet. Information representing the content is input into a hidden layer sequence of the ANN; information representing the contextual attributes is input into another hidden layer sequence of the ANN. Additionally or alternatively, a weighing engine determines a topical sentiment score by aggregating weighted conversation snippet sentiment scores. Weights to be applied to the conversation snippet sentiment scores may be determined based on, for example, a proportion of conversation snippets associated with the same topic that are conducted on a particular conversation channel as compared with other conversation channels, and respective roles of users participating in the conversation snippets conducted on the particular conversation channel.