Eurostar collects feedback through multiple channels, one of the most popular is
What it does
SentiRail scrapes historical data and collects new in real time. Using natural language processing algorithms, we derive context like WiFi issues, delays, refunds requests, etc. On top of that, we calculate the sentiment which is the measure which tells us whether the feedback is positive or negative. We significantly reduce manual labor of social media specialists by automatically replying on
The dashboard helps to visualize insights in real time and provides access to the historical data. Through
Slack the integration we can send live notifications to the support team as soon as possible.
How we built it
Data science part and NPL is done in
Python using polyglot and
Azure Cognitive Services. Web servers for
Slack integration are written in
Node.js. The dashboard is using
Challenges we ran into
Twitter API has a limit to how old data you can fetch so some data scraping was required. Firestore has some limitations regarding listening on entire datasets so we had to prepare an access policy for dashboard and web apps.
Accomplishments that we're proud of
It actually works, even in real time. It's deployed and publicly accessible.
What we learned
- Experience comparing AWS vs. Azure Cognitive Services
- Firestore real-time database on Google Cloud Platform
- Slack API