Farhan Hossain

Ramadan Mubarak!

I have come back after a MONTH of inactivity (Had a lot of summer programs that I had to apply for and FRC). However, we do have the feedback system through Postgres, and I think I am ready for deployment and making a demo

At this point, I will work on

• Deploying using Render and vercel
• Documentation and code cleanup

Stuff for the future???:

• Tune the model or switch to neural networks (if it’s any better)
• Learn Docker to containerize the project
• Use other social media platforms (if I get the data and the api isnt horrid)
• Make it easier for others to get set up on the project

There also seems to be a bug, or something wrong with the Twitter API. Sometimes, when you make a request, it returns an error that says the servers for the API are full. Maybe there are better alternatives to the X API, or I will consider buying a membership if the project is actually serious.

I finally made my homepage! It looks pretty basic but for classifying tweets being its only task, I would say it is suitable. I didn’t really work with the machine learning model, but here is stuff I would like to add:

• Notification system showing an error in the user’s request, or rate limits (Twitter being stingy with 1 classification per 15 minutes :/ )
• Possibly other forms of social media (Thinking about reddit)
• A feedback system where if the classification is right, the user can put a thumbs up, and a wrong classifcation for a thumbs down, to be stored in postgres and then train the model better

Also, I did get cooked on the report card lmao

New updates!

• Used X’s API to use twitter links instead of tweet text for a more convenient classification
• Now predictions show confidence, however new tweets are uncertain (in the images)
• Used Logistic Regression instead of Naive Bayes (Works a lot better by ~2% on accuracy and precision, and ~3% on F1 score and recall)
  To work on:
• I have settled on Logistic Regression, changing models will not do too much, and I am better off fine tuning the model for better classification on newer posts (Anything remotely political is classified as misinformation 😭)
• Obviously work on the website, I have put off on this for a while
  Also pray for a miracle on my report cards im lowkey cooked lol

I’ve been slacking off a bit due to midterms, but I am back! Today I added the integration to a frontend. And I realized Naive Bayes doesn’t work too well for classifying Twitter/X posts. These two classifications were cherrypicked.

Next:

• Try different models like Logistic Regression
• Improve frontend
• Integrate X/Twitter API so users can send links instead of the tweet text

Happy new year everyone! I finally found a dataset for my naive bayes model, however it is performing considerably worse. Idk if I will switch to something like logistic regression or smth, but for now I have it on flask

Finished working on the actual model, looks pretty good for news, but I haven’t tested for X/Twitter posts yet.

Worked on preprocessing the tweets for the first day, and I am currently researching how the Multinomial Naive Bayes model works

I’m working on my first project! This is so exciting. I can’t wait to share more updates as I build.