An Improved Model for Dynamic Opinion Updates in Online Social Networks

Online Social Networks play important role for the spread of social information, ideas and influence among its members. Investigation of Opinion dynamics in an online social network has been an important research challenge. Social influence is the process by which individuals may change their behavior, opinion, and beliefs, as a result of social interactions with other people. In this work, we investigate how social interactions change the shape of the opinion space. The parameters such as biasness, convincing power and sentiment are used to determine the opinion value. We have designed a dynamic opinion model called Difference Model, to determine the updated opinions of the users. Further, we have also performed the sentiment analysis of an opinion along with opinion dynamics to obtain the final opinion. The efficacy of the approach has been shown through experimentation and dynamic changes in opinion updates are obtained.