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