Business owners and content creators should exploit web scraping and NLP models to extract meaningful data from textual data from the web to boost their traffic and outrun their competitors.
The need of creating trending content, being in the form articles, videos or podcast episodes, is essential in outperforming competitors and feeding the audience with up-to-date information. This project was born out of the necessity of aiding clients in their content creation campaign by providing a list of possible trends in the respective niche that followed certain criteria.
Hence, project Palantìr was born. Today I am currently leading the project in my position of Lead Data Scientist in Pro Web Consulting, together with two developers taking care of the software architecture and infrastructure.
The project is now in Alpha version, and is planned to launch in December 2021.
Goal of the project 🎯
The aim of this project is to extract data from the web and to devise an algorithm capable of separating signal (possible trending topic) from noise. This should be done according to niche and source.
The trending topics would be delivered to the client and content would be created around that topic. This content would then be published on the client's website to leverage the hotness of the trends with the aim of gaining stronger traction and resonance from organic traffic.
- Data Scientist (me)
- Project manager (me)
- Backend developer
- Frontend developer
- Graphic designer
- UX designer
The software offers the following features
- topic extraction from several online social media, like Reddit and Twitter
- trending score according to several KPIs
- outlier removal
- auto-training upon every new detection
- data export in several formats
- SEO-enriched reports
- and much more