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Teenagers Sentiment Analysis from Social Network Data

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Social Networks Science: Design, Implementation, Security, and Challenges

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 few deep learning implementation techniques known as Convolutional Neural Network and Recursive Neural Network with classification of different texts.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, East West University, Dhaka, Bangladesh

    Lizur Rahman, Golam Sarowar & Sarwar Kamal

Authors
  1. Lizur Rahman
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  2. Golam Sarowar
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  3. Sarwar Kamal
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Corresponding author

Correspondence to Sarwar Kamal .

Editor information

Editors and Affiliations

  1. Department of Information Technology, Techno India College of Technology, Kolkata, West Bengal, India

    Nilanjan Dey

  2. Department of Information Systems, ISCAP, Porto Polytechnic, Porto, Portugal

    Rosalina Babo

  3. Department of Electronics and Electrical Communications Engineering, Faculty of Engineering, Tanta University, Tanta, Egypt

    Amira S. Ashour

  4. Department of Computer Science and Engineering, Ambedkar Institute of Advanced Communication Technologies and Research, New Delhi, India

    Vishal Bhatnagar

  5. Research Lab Sciences and Technologies of Image and Telecommunication, Sfax University, Sfax, Tunisia

    Med Salim Bouhlel

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Rahman, L., Sarowar, G., Kamal, S. (2018). Teenagers Sentiment Analysis from Social Network Data. In: Dey, N., Babo, R., Ashour, A., Bhatnagar, V., Bouhlel, M. (eds) Social Networks Science: Design, Implementation, Security, and Challenges . Springer, Cham. https://doi.org/10.1007/978-3-319-90059-9_1

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  • DOI: https://doi.org/10.1007/978-3-319-90059-9_1

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