Project Name: Sentiment Analysis of Tweets
Author: Christopher Goh Zhen Fung
- Email: chrisgzf@gmail.com
- LinkedIn: https://www.linkedin.com/in/chrisgzf/
- GitHub: https://github.com/chrisgzf
This project is about sentiment analysis of online tweets. I would like to train a neural network to be able to recognise if tweets (or text in general) sound happy or sad.
Why did I decide to work on this project: In recent years, there has been an unsettling trend of deteriorating mental health. If you browse social networks like Twitter, Reddit, Tumblr, you will realise that many depressed individuals have been going online to talk about their depression. In these cases, it is very common for other netizens to show concern to these individuals, often suggesting means to get help. With this tool, perhaps social workers can identify these at-risk individuals sooner and provide these individuals with care and companionship before they go over the edge.
Parts to this Project
- Trying out sentiment analysis on an already available airline twitter sentiment dataset
- Mining & data wrangling of tweets with Twitter Search API
- Sentiment analysis on these "mood tweets"
Credits: I would like to thank Sam & Martin from Red Dragon AI for giving a very comprehensive and well-run deep learning jump start workshop, where I learnt the skills required to work on this project.
Please do feel free to point out any mistakes or provide me with any suggestions!