Teenagers Sentiment Analysis from Social Network Data

8Citations
Citations of this article
7Readers
Mendeley users who have this article in their library.
Get full text

Abstract

Now a day’s social networks generate a huge data from user view, emotions, thoughts, opinions, suggestions regarding different products, events, places, brands, politics etc. Those data plays an important role in different ways. Technically, in the interval of every 60 s in a social network like Facebook, lots of comments and statuses are updated which are associated with thousands of contexts. However, realization of different ways in which texts are seems to be appeared on Facebook can help us to improve our products. In general, different organizations such as text organization used sentimental analysis for successful classification. They transpired feelings, emotions in different form like positive, negative, friendly, unfriendly etc. To solve this problem we have concentrated on different techniques of deep learning. In this paper we highlight about fewdeep learning implementation techniques known as Convolutional Neural Network and Recursive Neural Network with classification of different texts.

Cite

CITATION STYLE

APA

Rahman, L., Sarowar, G., & Kamal, S. (2018). Teenagers Sentiment Analysis from Social Network Data. In Social Networks Science: Design, Implementation, Security, and Challenges: From Social Networks Analysis to Social Networks Intelligence (pp. 3–23). Springer International Publishing. https://doi.org/10.1007/978-3-319-90059-9_1

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free