smyte.

Case Study

“Smyte has helped raise the value of our existing features, improving the quality of interactions between our members by eliminating contextually inappropriate content, messages, and fraudulent profiles.”

Jenn Louie
Head of Trust and Safety

Use Case

Social Network Spam

Meetup is the world’s largest social network of local groups. Meetup makes it easy for anyone to organize a local group or find one of the thousands already meeting up face-to-face. More than 9,000 groups get together in local communities each day, each one with the goal of improving themselves or their communities.

Challenges Meetup Faced

When you’re as well known as Meetup, you’re a draw for millions of happy members discovering new Meetups, making friends and enjoying a high quality of discourse. It’s important to accelerate the scalability, and improve the agility and adaptability of ongoing efforts to prevent blackhats who attempt:
  • Dating spam
  • Romance scams
  • Commercial solicitations
  • Fake profiles
  • Abusive messages

Solutions with Smyte

Smyte dedicated time and effort in getting to know Meetup’s vast, complex data set.
  • In relatively short order, we came up with a set of technologies to solve their use cases. In addition to creating NLP models, custom feature extraction and rules, we evaluated reputations and assessed relations for a wide variety of entities.
  • The aforementioned custom rules were created to handle a number of specialized use cases. Smyte and Meetup both have the ability edit these rules, create new ones, and push them to production. Real-time classification results have excellent precision.
Meetup takes full advantage of our analytics and manual review tools to power through review of suspicious actions.
  • Actions are automatically labeled with human-readable details of what’s questionable about the content, user, machine, IP etc.
  • Batch actions let customer success rapidly block or allow large numbers of related actions with a single click.
  • Emerging fraud campaigns are easily spotted through analytics graph trends.

Use Case

Social network spam

Learn More

Use Case

Cyberbullying

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Use Case

P2P fraud

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