Nudity Detection and Abusive Content Classifiers — Research and Use Cases

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Web 2.0 revolution has led to the explosion of content generated every day on the internet. Social sharing platforms such as Facebook, Twitter, Instagram etc. have seen astonishing growth in their daily active users but have been at their split ends when it comes to monitoring the content generated by their users. Users are uploading inappropriate content such as nudity or using abusive language while commenting on posts. Such behavior leads to social issues like bullying and revenge porn and also hampers the authenticity of the platform. However, the pace at which the content is generated online today is so high that it is nearly impossible to monitor everything manually. On Facebook itself, a total of 136,000 photos are uploaded, 510,000 comments are posted and 293,000 statuses are updated in every 60 seconds. At ParallelDots, we solved this problem through Machine Learning by building an algorithm that can classify nude photos (nudity detection) or abusive content with very high accuracy.