Nestor Alvaro (Data Scientist at Deloitte Digital, Spain)
Identifying political actions and locations in the news

Date: July 27, 2018
Time: 16:00 - 18:00 (Japan Time)
Venue: UTokyo, Komaba Campus, Building 2, Room 303
Language: English

Processing large quantities of news in a fast way requires automated techniques typically done by using machine learning algorithms. In this workshop we are going to see the most common methods for understanding the meaning underlying in the texts:

- In one hand, we will extract the different components in the news from a linguistic point of view, identifying verbs, nouns, adjectives, etc...
- On the other hand, we will explore the news from a conceptual point of view, identifying the main entities: organizations, people and locations.

By combining these methods we can analyze a subset of news containing political actions to extract insights underlying in these texts.

Nestor Alvaro is a Data Scientist at Deloitte Digital researching on machine learning (ML) and natural language processing (NLP).

*Supported by JSPS KAKENHI, Project/Area Number 15KT0040  (Takeshi Wada, The University of Tokyo)