Miss Representation
Inspiration
Many netizens justify hate speech and bias by quoting "Freedom of Speech". It is time we too use this right to battle misrepresentation of women and biases against them. This project will analyze social media content to promote safer spaces online and hold people accountable for their actions.
What it does
This project will take any text (be it a Tweet, article text, etc.) copied and pasted by the user OR a YouTube video link, and it will analyze the sentiment towards women in it.
How we built it
Technologies used include:
- Python
- ReactJS
- HTML
- CSS
- Gemini
- Speech-to-text transcription technologies
Gemini AI also helped us with basic code templates, debugging, idea suggestions, etc.
Challenges we ran into
-Due to lack of experience, changes in the free Twitter API, and time constraints, a proposed Twitter bot could not be completed. For this, users on the website could add the Twitter post link and its respective user's ID, and then the bot would use the Gemini API to understand the sentiment about women in that tweet and post about it. -Another proposed concept was to use Computer Vision (Open CV libraries) and Machine Learning to decode advertisements/movie scenes/YouTube videos better by analyzing facial expressions.
Accomplishments that we're proud of
- This was my first project on such a scale, and I am happy to have completed the main concept code for it.
- This idea is highly scalable and can be integrated into other systems.
- The project will point out instances of bias and hate against women, helping with online safety and promoting equality.
What we learned
I took a deeper dive into Frontend development and learned more about using AI APIs in projects.
What's next for Miss Representation
Since this project is highly scalable, the next step would be adding more features like bot integration, collaborations (HR management, interview policing, etc.) and hosting this website online.
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