Title :
Sentiment Analysis of Social Network Content
Author :
Shambhavi Dinakar;Pankaj Andhale;Manjeet Rege
Author_Institution :
Rochester Inst. of Technol., Rochester, NY, USA
Abstract :
Online social networking has an unparallel global audience and ranks as the highest type of online activity. It offers a platform for the audience to connect online and avoid the idiosyncrasies of personal one-on-one interaction. Over the course of time, online interaction has formed a culture of its own and has altered interpersonal communication of individuals, communities and societies all over the world. Recent psychology research sheds light on the negative aspects of such interaction. These include psychological disorders, cyber bullying, antisocial behaviors, depression, etc. By analyzing the vast amount of personal content that is freely available online, it is possible to analyze the behavioral and psychological balance of an individual. Thus, the data one chooses to make publicly available can be mined for information about ones own well being and mental balance. In this paper, we have performed sentiment analysis of online social activities of an individual which is then further analyzed to cluster behavioral and psychological tendencies of the individual.
Keywords :
"Sentiment analysis","Twitter","Mood","Data collection","Data visualization"
Conference_Titel :
Information Reuse and Integration (IRI), 2015 IEEE International Conference on
DOI :
10.1109/IRI.2015.37