Hey folks! I’m trying to figure out how to monitor and analyze the mood of tweets about my company. I want to set up a system that grabs mentions from Twitter, puts them in Airtable, and checks if they’re positive or negative.
I’ve got a Twitter dev account and I’m thinking of using Make (used to be called Integromat) to connect everything. But I’m not sure where to start or how to set it all up.
Has anyone done something like this before? What steps should I take? I’m especially curious about:
- Setting up the right fields in Airtable
- Using Make to grab tweets and send them to Airtable
- How to do the sentiment analysis part
Any tips or advice would be super helpful! I’m pretty new to this kind of automation stuff, so even basic pointers would be great. Thanks!
hey, i’ve done smthing similar! for airtable, use fields like tweet content, user handle, date, and sentiment score. make is great for connecting twitter to airtable. for sentiment analysis, try textblob - its a python library thats pretty easy to use. you can set up a simple script to analyze tweets and update airtable. good luck with ur project!
I’ve implemented a similar system for my company, and it’s been quite insightful. For Airtable, I’d recommend setting up fields for tweet text, user, timestamp, and sentiment score. In Make, you can use the Twitter module to fetch mentions and the Airtable module to add them to your base. The trickiest part is sentiment analysis. I ended up using a third-party API like IBM Watson or Google Cloud Natural Language for this. You’ll need to send each tweet through the API and then update the Airtable record with the sentiment score. It takes some trial and error to get it right, but once it’s set up, it’s incredibly useful for tracking brand perception in real-time. Just be prepared for some initial setup costs and ongoing API fees.
I’ve actually implemented a similar system for a client recently. One thing I found super helpful was using Zapier instead of Make – it has a more user-friendly interface for Twitter integrations. For Airtable, don’t forget to include fields for engagement metrics like retweets and likes. They can provide valuable context alongside sentiment.
For sentiment analysis, I’d recommend looking into Azure Cognitive Services. Their Text Analytics API is pretty powerful and easy to integrate. You can set up a simple Azure Function to process the tweets and send results to Airtable.
Word of caution: Twitter’s API can be finicky with rate limits. Make sure to implement proper error handling and maybe add a buffer system to avoid losing data if you hit limits. Also, consider adding a manual review step for borderline sentiment cases – AI isn’t perfect at catching nuances like sarcasm yet.
Hope this helps! Let me know if you need any clarification on the setup process.