Analyzing Domestic Violence and Online Harassment During COVID19
In this project, award-winning Red Dot Foundation partnered with Omdena to apply various AI and NLP tools to better understand domestic violence and online harassment trends during COVID19.
The problem: A rise in domestic violence
COVID19 has shown a marked increase in cases of domestic violence and online harassment. Data substantiating domestic violence from government resources are only available in summary form. Incidents increases are largely reported via calls and hence making data and subsequent mapping difficult. Also, online harassment is on the rise and that information is available anecdotally. Both problems need urgent attention!
The solutions
Based on initial social media and keyword searches provided by Red Dot, Omdena’s collaborators built an NLP classifier model by mining thousands of multi-lingual posts from Twitter, Reddit, YouTube, and news articles as well as government reports and Google trends. The team delivered the model, a labeled dataset, and Tableau workbook.
The impact
With this additional data, Red Dot was able to file public interest litigation with the Supreme Court of India. Their case was referred to the Ministry of Home Affairs and Omdena’s results formed part of the evidence base for their request to declare DV services as essential and issue guidelines.
Your benefits
Working with world-class mentors and domain experts to acquire real-world experience
Making international friends in a fast-growing supportive community of collaborators
Boosting your technical skills, problem-solving capabilities, and collaboration skills
Building your personal brand and publishing your own articles on our website and blog
Receiving certificates of participation and references to accelerate your career
Requirements
Good English
A good/very good grasp in computer science and/or mathematics
Student, (aspiring) data scientist, AI engineer, data engineer
Programming experience with C/C++, C#, Java, Python, Javascript or similar
Understanding of ML and Deep learning algorithms
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