The week's pick
Reseach Article
Identifying Human Personalized Sentiment with Streaming Data
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 160 - Number 7 |
| Year of Publication: 2017 |
| Authors: F. M. Tanvir Hossain, Maruf Ahmed, Anik Saha, Khandaker Tabin Hasan |
10.5120/ijca2017913088
|
F. M. Tanvir Hossain, Maruf Ahmed, Anik Saha, Khandaker Tabin Hasan . Identifying Human Personalized Sentiment with Streaming Data. International Journal of Computer Applications. 160, 7 ( Feb 2017), 26-31. DOI=10.5120/ijca2017913088
Abstract
Nowadays, social networks are becoming common platform of our emotion, sentiment, personality, and so on. A significant number of studies are also available about sentiment and emotion analysis from social network data. We observe that there are few studies are available those compute sentiment over real time data in Twitter and Foursquare. In this paper, we have conducted a research that can compute sentiment from real time data in a social network. We also use multiple techniques to compute sentiment such as sentiwordnet and textblob. We analyze the sentiments of a human from his/her twitter and from the location in foursquare of that person.
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