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Real-Time Social Media Monitoring with Artificial Intelligence
Confluent enables brands to better protect their reputations by streaming, processing, and governing social media data in real time.
Catch Posts Before They Go Viral
Social media has fundamentally changed brand management. A single viral post has the ability to significantly damage a brand’s reputation and cause its share price to tumble. To mitigate this risk, PR teams need to have visibility of potentially damaging posts as they happen.
Traditional approaches to social media monitoring have prevented this. Reliant on manual processes and batched data transfer, these approaches have resulted in PR teams only becoming aware of negative posts once they’ve become viral; by that time, the damage has already been done. Data streaming and Artificial Intelligence provides a solution to this dilemma.
Identify potentially damaging posts before they go viral.
Manage reputation crises more effectively, having identifying them earlier.
Maintain customer loyalty, having protected their reputations.
Build with Confluent
This use case leverages the following building blocks in Confluent Cloud.
Reference Architecture
This diagram shows a simplified Confluent Cloud architecture for streaming, processing, and governing media (image) and text data from Instagram in real time, in order to arrive at a “weighted aggregate” post score.
Python client hosted on AWS Lambda used to extract data from Instagram and load into Confluent topic.
Stream processing is used to manipulate and aggregate data to calculate a “weighted score.”
Schema Registry used to validate consistency of streaming data between systems.