An Empirical Study on Comment Classification

Due to increasing technologies in the interactive web applications, there has been a lot of development in E commerce and online social networking activities. The comments or the post always plays a vital role in understanding of the attitude towards a particular topic, product of the online users. Most of the times these comments or posts help the other users to understand the scenario and to take the right decision on the web platform. Machine learning plays a vital role to understand and to estimate the accurate semantics of these posts and comments. Natural language processing is widely used for this, Most of the times natural language processing does not yield much expected results in the classification of these comments due to the complexity in the narration. These complexities generally arise either due to poor narration of the comments or highly sarcastic contents in the comments. So to overcome these problems this paper broadly studies all the past work on comment classification and try to find the new way of machine learning to get the highly classified labels of the comments. Shubham Derhgawen | Rajesh Tak | Subhasish Chatterjee "An Empirical Study on Comment Classification" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-6 , October 2019, URL: https://www.ijtsrd.com/papers/ijtsrd28053.pdf Paper URL: https://www.ijtsrd.com/computer-science/artificial-intelligence/28053/an-empirical-study-on-comment-classification/shubham-derhgawen