POLITICALLY CORRECT SENTIMENT ANALYSIS OF ITALIAN POLITICAL TEXTS Roberto Reale, DDI 2019
The future offers very little hope for those who expect that our new mechanical slaves will offer us a world in which we may rest from thinking.
— Norbert Wiener, God & Golem, Inc., 1964
ARTIFICIAL INTELLIGENCE AND POLITICS
MAJOR TOPICS
influence governance transparency analytics
SENTIMENT ANALYSIS
The use of computational methods to systematically identify, extract, quantify, and study affective states and subjective information.
TOOLS
natural text
language processing
analysis
computational biometrics
linguistics
THE “MANIFESTO” PROJECT
THE MANIFESTO PROJECT
The Manifesto Project provides the scientific community with parties’ policy positions derived from a content analysis of parties’ electoral manifestos.
It covers over 1000 parties from 1945 until today in over 50 countries on five continents.
COLLECTIONS
Countries: Democratic countries, mostly member countries of the OECD.
Elections: Parliamentary (lower house) elections since the first democratic election in a country.
Parties: Programs of parties that gained at least one seat in parliament.
Documents: An authoritative document enacted and published by a party before an election that outlines a party’s policy plan for the time after the election and covers a broad range of policy issues.
TRAINING AND RULES
ď‚„
The coding (or annotation) is conducted by country experts.
ď‚„
The country expert coders are mostly political scientist or political science students and native speakers.
STRUCTURE OF THE MAIN DATASET
Each row in the dataset represents one electoral program.
The variables party and date jointly uniquely identify every row in the dataset.
It covers 4282 manifestos issued at 715 elections in 56 countries.
RES PUBLICA
DATA SETS
Italian
Parliament
Manifesto
texts of political parties
BOW VECTORIZATION
Segmentation Tokenization
into semantic units
into Bag-of-Words vectors
A PROOF-OF-CONCEPT
A
web app has been developed, as a fork and evolution of the “fipi” project.
Predicts
articles.
political views of texts and newspaper
A PROOF-OF-CONCEPT
Downloads, parses, and analyzes political articles from six major Italian newspapers on the whole political spectrum
Corriere della Sera
Il Fatto Quotidiano
il Giornale
Libero
la Repubblica
Il Sole 24 Ore
A PROOF-OF-CONCEPT
Based
on Python (flask, scipy, scikit-learn, pandas and bs4), Docker and AWS Elasticbeanstalk.
Code
available on GitHub
SOFTWARE
https://reale.me/respublica https://github.com/reale/respublica
HTTPS://REALE.ME/RESPUBLICA
ROBERTO@REALE.ME