A Horizon for Sentiment Analysis in Social Networks based on Interpreting Contents
Subject Areas : AI and Robotics
Maryam Tayefeh Mahmoudi
1
,
َAmirmansour Yadegari
2
,
Parvin Ahmadi
3
,
Kambiz Badie
4
1 - Data Analysis & Processing Research Group, IT Research Faculty, ICT Research Institute, Iran
2 - ICT Research Institute
3 - Data Analysis & Processing Research Group, IT Research Faculty, ICT Research Institute, Iran
4 - E-Content & E-Services Research Group, IT Research Faculty, ICT Research Institute, Iran
Keywords: Interpreting content, sentiment analysis, social network, content's narrator, rule-type protocol,
Abstract :
Interpreting contents in social networks with the aim of analyzing the sentiment of their narrators is of particular significance. In this paper, we present a framework for such a purpose, which is able to classify the messages hidden in contents based on using some rule-type protocols with high abstraction level. According to this framework, items such as prosodic of a content's narrator, context of disseminating a content and the key propositions in a content's text are regarded in the condition part of a protocol, while the possible classes for the message in a content are considered as its action part. It is to be noted that the proposed rule-type protocols can equally be used for other languages due to the generic-ness of the above-mentioned items. Results of computer simulations on a variety of different contents in the social networks show that the proposed framework is sufficiently capable of analyzing the sentiment of the contents' narrators in these networks.
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