On the interview of famous anchor Ranjini Haridas, she said that social networks such as facebooks are the platform to post unncessary posts. In her interview she told that actuall her post are filled with truly saying naughty words. And this will be the case of all popular stars. We found that still facebook hasn't solved this problem. That's why I choose a topic inorder to filter out the comment if the user desires only. That is it will be deactivated if it is not activated. Hence no violation of freedom to talk over facebook.

What it does: It will extract the comment for the post and predict whether the given comment is spam or not spam. Accordingly the the program will take the action using text

How I built it: It is build in Python. Uisng textblob I have the train the dataset with 0 and 1 corresponding to spam or not spam. The comment extracted from facebook is given to this model and predict. Accordingly if the algorithm found the comment is spam a small window will pop up. First we decided to delete the comment. But due short of time we couldn't complete it. So If the posted comment is spam it will pop out the window automatically saying that someone has posted a spam. Only post id '2021884018095792' is taken into consider

Challenges I ran into: Most challenges I found that availability of data. I tried to do in a way of wordvectors but couldn't touch to the last.

Accomplishments that I'm proud of: Now I can say that there won't be any unnecessary post on the facebook. The facebook public pages are visible to whole society. So they can post anything felt in their mind. So this will be a apt solution for that

What I learned: This problem can be solved easily.

What's next for Natural language processing for filtering out comments

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