Interpreting contents with the aim of analyzing the sentiment of their narrators in social networks, holds a high significance due to the role of a content in disseminating information to the corresponding human groups. In this paper, we propose a framework for analyzin More
Interpreting contents with the aim of analyzing the sentiment of their narrators in social networks, holds a high significance due to the role of a content in disseminating information to the corresponding human groups. In this paper, we propose a framework for analyzing sentiment on complex contents in a social network according to which a set of if-then type rules defined at high abstraction level, would be able to classify the messages behind these contents. According to this framework, items such as prosodic, context and key propositions are considered in the condition part of a rule and possible classes of message are taken into account in a rule’s action part. It is to be noted that the rules proposed for interpreting a content do not depend on the considered language due to the very inherent property of the items which are considered in interpretation. Results of experiments on a wide range of different contents in a social network support the fact that the proposed framework is sufficiently capable of analyzing the sentiments of contents’ narrators.
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