get_ECB_speeches

This helper function automatically retrieve the full data set of
speeches made available by the ECB. In addition, it implements a number of
pre-processing steps that may be turned on or off as needed.

A framework that joins topic modeling and sentiment analysis of
textual data. The package implements a fast Gibbs sampling estimation of
Latent Dirichlet Allocation (Griffiths and Steyvers (2004)
<doi:10.1073/pnas.0307752101>) and Joint Sentiment/Topic Model (Lin, He,
Everson and Ruger (2012) <doi:10.1109/TKDE.2011.48>). It offers a variety of
helpers and visualizations to analyze the result of topic modeling. The
framework also allows enriching topic models with dates and externally
computed sentiment measures. A flexible aggregation scheme enables the
creation of time series of sentiment or topical proportions from the enriched
topic models. Moreover, a novel method jointly aggregates topic proportions
and sentiment measures to derive time series of topical sentiment.

Olivier Delmarcelle

sentopics

Tools for Joint Sentiment and Topic Analysis of Textual Data

Samuel Borms

Chengua Lin

Yulan He

Jose Bernardo

David Robinson

Julia Silge

get_ECB_speeches function

<dl><dt>filter_english</dt>
<dd>if <code>TRUE</code>, attempts to select English speeches only
using <code>textcat::textcat()</code>.</dd>
<dt>clean_footnotes</dt>
<dd>if <code>TRUE</code>, attempts to clean footnotes from speeches
texts using some regex patterns.</dd>
<dt>compute_sentiment</dt>
<dd>if <code>TRUE</code>, computes the sentiment of each speech
using <code>sentometrics::compute_sentiment()</code> with the the Loughran &amp; McDonald
lexicon.</dd>
<dt>tokenize_w_POS</dt>
<dd>if <code>TRUE</code>, tokenizes and apply Part-Of-Speech tagging
with <code>spacyr::spacy_parse()</code>. Nouns, adjectives and proper nouns are then
extracted from the parsed speeches to form a <code>tokens</code> object.</dd></dl>

Arguments

Download and pre-process speeches from the European Central Bank — get_ECB_speeches

<dl>

<dt>filter_english</dt>
<dd>if <code>TRUE</code>, attempts to select English speeches only
using <code>textcat::textcat()</code>.</dd>


<dt>clean_footnotes</dt>
<dd>if <code>TRUE</code>, attempts to clean footnotes from speeches
texts using some regex patterns.</dd>


<dt>compute_sentiment</dt>
<dd>if <code>TRUE</code>, computes the sentiment of each speech
using <code>sentometrics::compute_sentiment()</code> with the the Loughran &amp; McDonald
lexicon.</dd>


<dt>tokenize_w_POS</dt>
<dd>if <code>TRUE</code>, tokenizes and apply Part-Of-Speech tagging
with <code>spacyr::spacy_parse()</code>. Nouns, adjectives and proper nouns are then
extracted from the parsed speeches to form a <code>tokens</code> object.</dd>

</dl>

get_ECB_speeches: Download and pre-process speeches from the European Central Bank

Description

Usage

Value

Arguments