Nowadays, Youtube is one of the most successful social networks, therefore it has more and more impact in our society.
Due to this it’s quite useful to know the sentiments that this platform videos produces.
This project has been focused in the development of a tool able to analise this sentiments, which could be used for different purposes like Market studies or emotional learning for people who has some functional diversity.
The technologies used during the project development has been:
- Luigi (Data extraction, formatting, analysis with senpy and sending to Elasticsearch.)
- D3.js (Analysed data displaying.)
- Polymer Web Components (Creation of reusable widgets for analysis displaying.)
The final result has been the creation of a sefarad-integrable dashboard which contains 3 widgets:
1) yt-video-widget: Displays the video which is going to be analised.
2) yt-sentiment-widget: Displays a graph with the results of the video subtitles analysis.
3) yt-comments-widget: Displays the video comments classified by the sentiment pro-