scholarly journals Exploring the political pulse of a country using data science tools

2020 ◽  
Author(s):  
Miguel Folgado ◽  
Veronica Sanz
Keyword(s):  
Political Parties ◽  
Data Science ◽  
The Political ◽  
Political Affiliation ◽  
Proof Of Concept ◽  
Human Communication ◽  
Use Of Data ◽  
Political Analysis ◽  
Using Data ◽  
Negative Sentiment

In this paper we illustrate the use of Data Science techniques to analyse complex human communication. In particular, we consider tweets from leaders of political parties as a dynamical proxy to political programmes and ideas. We also study the temporal evolution of their contents as a reaction to specific events. We analyse levels of positive and negative sentiment in the tweets using new tools adapted to social media. We also train an Artificial Intelligence to recognise the political affiliation of a tweet. The AI is able to predict the origin of the tweet with a precision in the range of 71-75%, and the political leaning (left or right) with a precision of around 90%. This study is meant to be viewed as a proof-of-concept of interdisciplinary nature, at the interface between Data Science and political analysis.

scholarly journals Exploring the political pulse of a country using data science tools

2022 ◽  
Author(s):  
Miguel G. Folgado ◽  
Veronica Sanz
Keyword(s):  
Political Parties ◽  
Data Science ◽  
The Political ◽  
Human Communication ◽  
Use Of Data ◽  
Political Analysis ◽  
Different Types ◽  
Using Data ◽  
Negative Sentiment ◽  
Fully Connected

AbstractIn this paper we illustrate the use of Data Science techniques to analyse complex human communication. In particular, we consider tweets from leaders of political parties as a dynamical proxy to political programmes and ideas. We also study the temporal evolution of their contents as a reaction to specific events. We analyse levels of positive and negative sentiment in the tweets using new tools adapted to social media. We also train a Fully-Connected Neural Network (FCNN) to recognise the political affiliation of a tweet. The FCNN is able to predict the origin of the tweet with a precision in the range of 71–75%, and the political leaning (left or right) with a precision of around 90%. This study is meant to be viewed as an example of how to use Twitter data and different types of Data Science tools for a political analysis.

scholarly journals How to Analyze Islamist Politics: Is it possible to make a Political Study without Sociology of Islam?

2019 ◽  
Author(s):  
Özgür Erden
Keyword(s):  
Political Parties ◽  
Political Institutions ◽  
Capital Accumulation ◽  
Economic Structure ◽  
The Political ◽  
Economic Factors ◽  
Political Movement ◽  
Political Analysis ◽  
Political Relations ◽  
The Social

This article embarks on making a political analysis of Islamist politics by criticizing the hegemonic approach in the field and considering a number of the institutions or structures, composing of either state and its ideological-repressive apparatuses, political parties and actors, intellectual leadership and ideology, and political relations, events, or facts in political sphere. The aforesaid approach declares that the social and economic factors, namely class position, capital accumulation, market, education, and culture, have been far better significative for a political study in examining any political movement, party, and fact or event. However, our study will more stress on political structures, events and struggles or conflicts produced and reproduced by the political institutions, the relationships and the processes in question. Taking into account all these, it will be argued that they have been more significant as compared to class position, capital accumulation, market in economic structure, or culture and education, in a political study.

Stemmen in Vlaanderen op 13 december 1987 : Een statistische analyse

Res Publica ◽  
1988 ◽  
Vol 30 (1) ◽  
pp. 25-50
Author(s):  
Marc Swyngedouw ◽  
Jaak Billiet
Keyword(s):  
Political Parties ◽  
Democratic Party ◽  
Occupational Status ◽  
The Political ◽  
Voting Behaviour ◽  
National Elections ◽  
Statistische Analyse ◽  
Use Of Data ◽  
Linear Modelling ◽  
Log Linear

Taking into account the limits of such data, this study analyses the shifts in voting behaviour from the national elections in 1985 to those in 1987 in Flanders, using log-linear modelling. The use of data from poll surveys for estimating shifts between subsequent elections poses some methodological problems.The second part presents the results of the analysis. About 13,51 % of -the 1985-voters switched. Although there are significant shifts between all the political parties, the Christian Democratic Party (CVP) loses on all fronts. A log-linear analysis of party-reference by sex, age and occupational status shows the strength and weakness of each party in different societal categories. In conclusion, an interpretation of the shifts is proposed. The following factors can account for the major shifts : the desintegration of the catholic pillar, the emergence of a dual society, the affinity between neo-liberalism and yuppie-culture and the conflict between the language communities.

Twitter and Political Elections

2012 ◽  
pp. 1018-1034
Author(s):  
Fabian Ströhle ◽  
Timm Sprenger
Keyword(s):  
Political Parties ◽  
Social Networking ◽  
The Political ◽  
Prediction Markets ◽  
Communication Behavior ◽  
Human Communication ◽  
The Future ◽  
Political Deliberation ◽  
Opinion Polls

The rise of Twitter has changed human communication behavior not only in the political domain, but also in many other fields. Individuals are increasingly using microblogging platforms like Twitter for political deliberation, making full use of the features offered for discussions and social networking. At the same time, politicians and political parties hop on the bandwagon, using Twitter to reach a larger audience and communicate to constituents. As is the case for blogs, the political Twittersphere is fragmented along party lines, but stimulates communication between different ideological clusters. The publicly available discussions on Twitter can serve as a basis for election forecasts and have the potential to complement opinion polls and prediction markets in the future.

The Mobilization of Campaign Activists By the Party Canvass

1999 ◽  
Vol 27 (2) ◽  
pp. 177-200 ◽  
Author(s):  
PETER W. WIELHOUWER
Keyword(s):  
Political Parties ◽  
Political Participation ◽  
Rational Choice ◽  
Political Behavior ◽  
Choice Model ◽  
The Political ◽  
Rational Choice Model ◽  
Using Data ◽  
Election Studies

This research examines the role of the personal contacting activities of the political parties as mobilizing forces in what Verba and Nie termed campaign activities. A reformulated rational choice model is discussed in which parties seek to reduce certain avoidable and unavoidable costs associated with political participation. Using data from the 1952 through 1994 American National Election Studies, it is shown that the party contact has been and continues to be a major factor in mobilizing campaign activists. Its influence is remarkably robust, maintaining statistical and substantive significance even after controlling for other important factors usually associated with political behavior.

scholarly journals Emergence of Ethnopolitical Journalism in Kenya: Lessons from the 2017 Televised Political Analyses Shows

2019 ◽  
Vol 1 (1) ◽  
pp. 36-51
Author(s):  
Michael M Ndonye
Keyword(s):  
Political Parties ◽  
Mass Media ◽  
Identity Formation ◽  
Ethnic Groups ◽  
Transformative Leadership ◽  
The Political ◽  
Presidential Candidates ◽  
Mainstream Media ◽  
Ethnic Identity Formation ◽  
Political Analysis

This paper critiques ethnopolitical journalism in televised political analyses of the 2017 electoral process in Kenya. Ethnopolitical journalism is a reporting model characterised by a focus on ethnicity when analysing and describing political situations; leading to ethnic identity formation in the society that places mass media at economic vantage point. Motivated by mediatized ethnicity, Kenyans find themselves perpetually under normalised ethnopolitics and ethnopolitical journalism is a major strategy in the mainstream media. Fourteen televised political analysis shows; from major television channels were examined. The analysis targeted prioritised and dominant topics of discussion, the composition of the panels; the most discussed presidential candidates and the moderator’s leads toward a particular direction during the analyses. The findings show that in all the televised political analysis shows, all members of the panel are drawn from the five ethnic groups. Moreover, all priority topics target the two supposedly major political sides (NASA and Jubilee); whose principals and deputies come from the five ethnic groups. It was also noted that every discussion from different Television channels are narrowed deliberately by the moderator to discuss about Raila Odinga and Uhuru Kenyatta, thus, ignoring all other presidential candidates, their political parties and areas considered their strongholds. These findings reveal the media’s deliberate choices of house styles and reporting models during the electoral periods in Kenya. The study concludes that media has been the high priest of ethnicity normalization culture that has shaped the political mindset of Africa to the extent of undermining its transformative leadership. The findings add to the research critical of media practice and political economy of mass media reporting during electioneering periods.

Validating and Improving Voting Advice Applications: Estimating Party Positions Using Candidate Surveys

2018 ◽  
Vol 9 (2) ◽  
pp. 135-160 ◽  
Author(s):  
Ioannis Andreadis ◽  
Heiko Giebler
Keyword(s):  
Political Parties ◽  
Party System ◽  
Political Competition ◽  
Party Competition ◽  
The Political ◽  
Additional Source ◽  
Policy Issues ◽  
Party Positions ◽  
Using Data ◽  
Voting Advice Applications

AbstractLocating political parties correctly regarding different policy issues is not just crucial for research on parties, party competition, and many similar fields but also for the electorate. For the latter, it has become more and more important as the relevance of voting advice applications (VAA) has increased and as their main usage is to compare citizens’ policy preferences to the offer of political parties. However, if party positions are not adequately assigned, citizens are provided with suboptimal information which decreases the citizens’ capacities to make rational electoral decision. VAA designers follow different approaches to determining party positions. In this paper, we look beyond most common sources like electoral manifestos and expert judgments by using surveys of electoral candidates to validate and improve VAAs. We argue that by using positions derived from candidate surveys we get the information by the source itself, but at the same time we overcome most of the disadvantages of the other methods. Using data for the 2014 European Parliament election both in Greece and Germany, we show that while positions taken from the VAAs and from the candidate surveys do match more often than not, we also find substantive differences and even opposing positions. Moreover, these occasional differences have already rather severe consequences looking at calculated overlaps between citizens and parties as well as representations of the political competition space and party system polarization. These differences seem to be more pronounced in Greece. We conclude that candidate surveys are indeed a valid additional source to validate and improve VAAs.

Party Competition and the Inter-Industry Structure of US Trade Protection

2016 ◽  
Vol 5 (3) ◽  
pp. 489-509
Author(s):  
Su-Hyun Lee
Keyword(s):  
Political Parties ◽  
Political Representation ◽  
Industry Structure ◽  
Party Competition ◽  
The Political ◽  
Marginal Effect ◽  
Declining Industries ◽  
Using Data ◽  
Strategic Allocation ◽  
Trade Preferences

Why do some declining industries receive more compensation through protectionist policies than others, even without actively engaging in lobbying? How does the political representation of industries affect their chances for protectionist relief? This paper argues that political parties seek to optimize electoral returns through the strategic allocation of distributive benefits generated by trade barriers. The inter-industry structure of protection is thus explained by the interaction between industries’ trade preferences and political characteristics. Using data on protection and subnational employment for US industries and district-level election outcomes in the 1990s, this paper finds that the concentration of industries in competitive constituencies not only increases their chances of receiving higher tariffs, but also magnifies the marginal effect of comparative disadvantage on tariff and nontariff protection.

scholarly journals Social Media Behavioral Intelligence using Feature Extraction

2021 ◽  
pp. 01-06
Author(s):  
Panchal Mayuriben ◽  
Dr. Priyanka Sharma ◽  
Jatin Patel
Keyword(s):  
Social Media ◽  
Feature Extraction ◽  
Political Parties ◽  
Research Work ◽  
Behavioral Pattern ◽  
The Political ◽  
The Social ◽  
Recent Trends ◽  
Bayes Algorithm ◽  
Using Data

Analysis of the behavioral pattern of a people using data of the social media became a trend in last couple of years. Among this popular network, Twitter, Facebook and the Instagram become more and more popular and that’s why these platforms attract the lots of researchers to predict the sentiment regarding major events like election, product brand, movie, stock market and recent trends are some of them. By identifying the attitude associated with the text in terms of positive, negative or the neutral we are able to analyze the opinion behind the content generated by the user and this opinions about the sentiment are very helpful to for the organization or the political parties or among other entities. The task of sentiment analysis is conducted using identifying the polarity associated with the word or document or we can say sentence. This paper consists research work which is designed to improve the accuracy of the model by improving the Naïve Bayes algorithm and I also worked to improve the 3-gram method during my research

Use of Data Analytics to Increase the Efficiency of Last Mile Logistics for Ecommerce Deliveries

2021 ◽  
pp. 167-180
Author(s):  
Gaurav Nagpal ◽  
Gaurav Kumar Bishnoi ◽  
Harman Singh Dhami ◽  
Akshat Vijayvargia
Keyword(s):  
Data Analytics ◽  
Data Science ◽  
Operational Efficiency ◽  
Use Of Data ◽  
Last Mile ◽  
Digital Transactions ◽  
Using Data ◽  
Operational Excellence ◽  
The Way

With the increasing share of digital transactions in the business, the way of operating the businesses has changed drastically, leading to an immense opportunity for achieving the operational excellence in the digital transactions. This chapter focusses on the ways of using data science to improve the operational efficiency of the last mile leg in the delivery shipments for e-commerce. Some of these avenues are predicting the attrition of field executives, identification of fake delivery attempts, reduction of mis-routing, identification of bad addresses, more effective resolution of weight disputes with the clients, reverse geo-coding for locality mapping, etc. The chapter also discusses the caution to be exercised in the use of data science, and the flip side of trying to quantify and dissect the phenomenon that is so complex and subjective in nature.

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