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approach to understanding Central Banks

 

A Big Data approach to understanding Central Banks / 1

A Big Data approach

to understand

Central Banks Big Data Spain 2018

November 2018

 

 

A Big Data approach to understand Central Banks / 2

Summary

01

02

Why is the use of NLP important in economics

and Monetary policy?

The data and methodology

Understanding Central Banks: “What”, “How”

and “Who” is talking (or writing) about?

 

 

A Big Data approach to understand Central Banks / 3

01 Why is the use of NLP important in

economics and Monetary policy?

 

The data and methodology

 

 

A Big Data approach to understand Central Banks / 4

of the total amount of web

pages on the internet is given

by textual or unstructured data

Text mining to extract meaning from

strings of letters

It helps us to understand

what drives monetary

policy decisions

The potential use of textual information and

text sources improves the understanding of

economic and financial systems

Why is the use of NLP important in economics and Monetary policy?

Text as a key source of information to enrich economic analysis

80%

 

 

A Big Data approach to understand Central Banks / 5

80% of available data

20% of used data

 

 

A Big Data approach to understand Central Banks / 6

The data and methodology

From Extraction to Sentiment Analysis

Information

extraction

Pre-Processing

and text parsing Transformation

Text mining

and NPL

Sentiment

analysis

Documents

Web pages

Extract words

Identify parts of

speech

Tokenization and

multi-word tokens

Stopword Removal

Stemming

Case-folding

 

 

Text filtering

Indexing to quantify

text in lists of

term counts

Create the

Document-term

matrix

Weighting matrix

Factorization

(SVD)

 

Analysis and

Machine learning

Topics extraction

(LDA)

Clustering

Modelling

(STM and DTM)

 

 

Apply sentiment

dictionaries

Semantic analysis

and classification

Clustering