Politics and Big Data

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A01=Andrea Ceron
A01=Luigi Curini
A01=Stefano Maria Iacus
age
analysis
analyzing
Antonio Di Pietro
Author_Andrea Ceron
Author_Luigi Curini
Author_Stefano Maria Iacus
Automated Sentiment Analysis
Big Data
Big Data Revolution
campaign
campaign data analytics
Category=JBCT
Category=JHB
Category=JPHF
Category=JPWC
Centre Left Primary
computational social science
Distributive Promises
elections
electoral
Electoral Forecasts
electoral prediction methods
eq_bestseller
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
eq_society-politics
evaluation
forcast
forecasting
forecasts
Fractional Logit
France
gender
IDV
intentions
Italian Political Leaders
Italy
Lead Lag Effect
media
meta-analysis in political science
momentum
monitor
Negative Campaign
Negative Campaigning
Nichi Vendola
nowcasting
online ideas
opinion
Pier Luigi Bersani
polls
public
public opinion modelling
race
recording
SASA
Sel
sentiment
Sentiment Analysis
sentiment analysis techniques
SNS Usage
social
social media
Social Media Analysis
Social Media Data
social media sentiment election forecasting
Social Media Users
survey
Survey Polls
trends
UDC
USA
voting
Voting Intentions

Product details

  • ISBN 9780367194550
  • Weight: 453g
  • Dimensions: 156 x 234mm
  • Publication Date: 08 Jan 2019
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Paperback
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The importance of social media as a way to monitor an electoral campaign is well established. Day-by-day, hour-by-hour evaluation of the evolution of online ideas and opinion allows observers and scholars to monitor trends and momentum in public opinion well before traditional polls. However, there are difficulties in recording and analyzing often brief, unverified comments while the unequal age, gender, social and racial representation among social media users can produce inaccurate forecasts of final polls. Reviewing the different techniques employed using social media to nowcast and forecast elections, this book assesses its achievements and limitations while presenting a new technique of "sentiment analysis" to improve upon them. The authors carry out a meta-analysis of the existing literature to show the conditions under which social media-based electoral forecasts prove most accurate while new case studies from France, the United States and Italy demonstrate how much more accurate "sentiment analysis" can prove.

Andrea Ceron is Assistant Professor at Università degli Studi di Milano, Italy, where he teaches Political and Administrative Systems, and Applied Multivariate Analysis for Social Scientists. His research focuses on intra-party politics, quantitative text analysis, media bias, and social media analysis. He has published a dozen of papers in international academic peer-reviewed journals like British Journal of Political Science, European Journal of Political Research, Party Politics, New Media & Society, Electoral Studies, Social Science Computer Review, Journal of Language and Politics, and others.

Luigi Curini is Associate Professor of political science at Università degli studi di Milano, Italy, where he teaches Political Science, Applied Multivariate Analysis for Social Scientists, Game Theory, and Analysis of Political Institutions. His research focuses on party competition, spatial theory of voting, and social media analysis. He has published over 30 papers in international academic peer-reviewed journals like Comparative Political Studies, Journal of Politics, British Journal of Political Science, European Journal of Political Research, Public Choice, Party Politics, European Political Science Review and many others.

Stefano Maria Iacus is Professor of mathematical statistics and probability at Università degli Studi di Milano, Italy. Member of the R Core Team for the deveolpment of the R statistical software. His fields of interest include computational statistics, theoretical statistics, inference for stochastic processes, text mining and sentiment analysis, and causal inference. He has published over 50 papers in international academic peer-reviewed journals.

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