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International Journal of Scientific & Technology Research

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IJSTR >> Volume 10 - Issue 2, February 2021 Edition



International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616



Sentiment Analysis: A Research Perspective

[Full Text]

 

AUTHOR(S)

Shafique Awan, Aijaz Ahmed Arain, Kashif Mehmood, Fida Hussain Khoso, Abdullah Ayub Khan

 

KEYWORDS

Sentiment analysis, Social networking apps, Facial expressions, Human emotions, Human feelings, Human thinking, Human behavior, Human psychology.

 

ABSTRACT

Nowadays, human sentiment analysis is one of the biggest challenges for computing technology researchers. Intelligent methods are used to capture human facial expressions then these expressions are analyzed by means of emotions, feelings, thinking, and behavior. Actually, it relates to human nature that can be observed and analyzed by person to person in a real-world environment. In this paper, we have proposed human sentiments analyses associate with social networking apps. These social networking apps must be built smarter so that they could interact with human sentiments. One of the widely used social networking web apps is Facebook, people used to connect, share their achievements, feelings, thinking, point of views, observations, and most probably emotions, through upload status, pictures, videos, and many other ways. We can achieve the goal by collaborating both fields such as human psychology and cognitive, possible to implement while connecting the camera with deep learning computing technology. Detecting and recognizing the real-time face image, analyzing facial expressions, and recommend activities according to the experimental outcomes of the analysis. The purpose is to generate an intelligent bridge between humans and computers which interact in a smart manner.

 

REFERENCES

[1] Tumasjan, A., Sprenger, T. O., Sandner, P. G., & Welpe, I. M. (2010, May). Predicting elections with twitter: What 140 characters reveal about political sentiment. In Fourth international AAAI conference on weblogs and social media.
[2] Haddi, E., Liu, X., & Shi, Y. (2013). The role of text pre-processing in sentiment analysis. Procedia Computer Science, 17, 26-32.
[3] Singh, T., & Kumari, M. (2016). Role of text pre-processing in twitter sentiment analysis. Procedia Computer Science, 89(Supplement C), 549-554.
[4] Pak, A., & Paroubek, P. (2010, May). Twitter as a corpus for sentiment analysis and opinion mining. In LREc (Vol. 10, No. 2010, pp. 1320-1326).
[5] Cataldi, M., Di Caro, L., & Schifanella, C. (2010, July). Emerging topic detection on twitter based on temporal and social terms evaluation. In Proceedings of the tenth international workshop on multimedia data mining (pp. 1-10).
[6] Thelwall, M., Buckley, K., & Paltoglou, G. (2011). Sentiment in Twitter events. Journal of the American Society for Information Science and Technology, 62(2), 406-418.
[7] Medhat, W., Hassan, A., & Korashy, H. (2014). Sentiment analysis algorithms and applications: A survey. Ain Shams engineering journal, 5(4), 1093-1113.