Youtube Video Ranking: A NLP based System
Selvakumar K1, Rajesh M2, Eshwar S3, Shraveen BS4
1Selvakumar K*, Computer Science and Engineering, Vellore Institute of Technology, Vellore, India.
2Rajesh M, Computer Science and Engineering, Vellore Institute of Technology, Vellore, India.
3Eshwar S, Computer Science and Engineering, Vellore Institute of Technology, Vellore, India.
3Shraveen BS, Computer Science and Engineering, Vellore Institute of Technology, Vellore, India.

Manuscript received on November 15, 2019. | Revised Manuscript received on November 23, 2019. | Manuscript published on November 30, 2019. | PP: 1370-1375 | Volume-8 Issue-4, November 2019. | Retrieval Number: D7303118419/2019©BEIESP | DOI: 10.35940/ijrte.D7303.118419

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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: YouTube is an acclaimed video information source on the web among various social media sites, where users are sharing, commenting and liking/dis-liking the video along with the continuous uploading of videos in real-time. Generally, the quality, popularity and relevance of results obtained from searching a query are obtained based on a rating system. Now and then few irrelevant and substandard videos are ranked higher because of higher views and likes. To address this issue, we put forth a sentiment analysis approach on the user comments based on Natural Language Processing. The suggested analysis will be helpful in providing a desirable result to the search query. The effectuality of the system has been proved in this paper using a data driven approach in terms of accuracy.
Keywords: Natural Language Processing, YouTube, Sentiment Analysis, Vader.
Scope of the Article: Natural Language Processing.