28/03/2023
Monitor Twitter activity in real time using Microsoft Azure -> Sentiment analysis -> Customer retention -> YOUR SUCCESS.
Tools: Azure Functions and Python
What can be added to this very quick:
Sentiment analysis and then ... you can start working on Customer retention = YOUR SUCCESS.
AI working for you is not a science rocket.
Azure Functions - serverless compute service that enables users to run event-driven functions in the cloud.
Creating a small, single-purpose functions that are triggered by events. In this case a post on Twitter.
The beauty of functions is that are automatically scaled and managed by the platform, so we don't need to worry about server infrastructure or resource allocation.
To detect when something was published on Twitter using Azure Functions, we use the Twitter API to monitor the Twitter stream for new tweets.
New tweets will trigger the Azure Function (eventually when matching certain criteria is detected).
General steps you can follow:
1. Create a new Azure Function and choose the appropriate trigger type: HTTP, Timer or Event Grid trigger.
2. Configure the Twitter API in the Azure Function using Twitter developer credentials and setting up a connection to the Twitter API using tweepy package for Python.
3. Write code in your Azure Function to monitor the Twitter stream for new tweets and filter the tweets based on certain criteria.
4. When a new tweet matching your criteria is detected, trigger your Azure Function and perform the desired actions: storing the tweet data in a database, sending a notification, or triggering another API
Where to start:
- Azure subscription.
- Twitter developer account.
- Tweepy: https://docs.tweepy.org/en/stable/
Need it implement for you (we do not touch your website)?
Contact us: https://www.olala.agency/contact and you will be HAPPY with the result.
