Title :
A sentiment analysis prototype system for social network data
Author :
Santidhanyaroj, Pitiphat ; Khan, T.A. ; Gelowitz, C.M. ; Benedicenti, L.
Author_Institution :
Fac. of Eng. & Appl. Sci., Univ. of Regina, Regina, SK, Canada
Abstract :
Social networks have become an on-line mechanism for individuals to express their feelings, emotions and perspectives on a wide variety of topics and events. They have also become resources for researchers who are interested in sentiment based analysis. There is a wealth of information made available via application programming interfaces (APIs) by popular social networks. This paper discusses a prototype system to enable automated opinion based analysis of social network data for evaluation of the public social conscience of user provided topics and events.
Keywords :
Bayes methods; application program interfaces; behavioural sciences computing; data handling; natural language processing; social networking (online); support vector machines; text analysis; API; Facebook; Twitter; application programming interfaces; automated opinion based analysis; naive Bayes; public social conscience evaluation; sentiment analysis prototype system; social network data; support vector machine; Accuracy; Facebook; Prototypes; Sentiment analysis; Support vector machines; Twitter; APIs; Facebook; Naive Bayes; Twitter; sentiment analysis; support vector machine;
Conference_Titel :
Electrical and Computer Engineering (CCECE), 2014 IEEE 27th Canadian Conference on
Conference_Location :
Toronto, ON
Print_ISBN :
978-1-4799-3099-9
DOI :
10.1109/CCECE.2014.6900951
