Online Human-Bot Interactions: Detection, Estimation, and Characterization

Understand

Increasing evidence suggests that a growing amount of social media content is generated by autonomous entities known as social bots.

• In this work we present a framework to detect such entities on Twitter.
• We leverage more than a thousand features extracted from public data and meta-data about users: friends, tweet content and sentiment, network patterns, and activity time series.
• We benchmark the classification framework by using a publicly available dataset of Twitter bots.