Students taking online lectures often find it difficult to get relevant videos on the topics of their interest.
They comment on several videos to persuade the content providers to make videos on these topics, but these comments are often not seen by the content providers.
In order to cater to the needs of the users, the comments on the various videos were analyzed.
Initially, the comments on the first 10 videos on a topic were classified on the basis of whether the comment actually contained a topic or not.
The comments chosen are then analyzed to extract keywords out of them. These keywords are then shown to the content Provider so that the can make a note of the topics that are in demand.
Netbeans IDE
Pycharm
https://developers.google.com/youtube/v3/
The user interface for this software is JAVA which was built on Netbeans IDE.
The comment classification using the Random Forest Algorithm that was implemented in Python
NLP for sentiment analysis.
Dandelion API was used for the keyword extraction that makes use of NER(Named Entity Recognition)
New Content Providers will be benefitted as they will get the topics in demand.
They can take up any of these topics based upon their interests.
Sentiment analysis score of the comments on videos are considered.