Parteikommunikation im Zeitalter von Social Media

2020 ◽  
Author(s):  
Mario Datts
Keyword(s):  
Social Media ◽  
Big Data ◽  
Political Parties ◽  
Explanatory Model ◽  
Election Campaigns ◽  
Data Set ◽  
Comprehensive Data ◽  
Party Members ◽  
District Offices

How active are the local branches of political parties on social media? Do such parties use social media on the training ground of democracy? This study answers these questions using a comprehensive data set consisting of big data and data from surveys. It identifies political parties’ key reasons for using social media by developing and examining a complex explanatory model, the results of which reveal that the majority of parties’ district offices are active on social media, for example on WhatsApp, Twitter and YouTube in addition to Facebook. One key reason for them using social media sites is their desire to meet the expectations of their own party members. Furthermore, they appear to use social media in their election campaigns and because of their general distrust of the conventional media’s reporting. What is noticeable is that the local divisions of the AfD in particular seem to be extremely successful in using social media.

scholarly journals Introduction to special issue about election reporting: Why journalism (still) matters

Journalism ◽  
2019 ◽  
Vol 20 (8) ◽  
pp. 985-993 ◽  
Author(s):  
Stephen Cushion ◽  
Daniel Jackson
Keyword(s):  
Social Media ◽  
Political Parties ◽  
Political Communication ◽  
News Media ◽  
Election Campaigns ◽  
Special Issue ◽  
Technological Advances ◽  
Campaign Coverage ◽  
Election Coverage ◽  
Social Media Platforms

This introduction unpacks the eight articles that make up this Journalism special issue about election reporting. Taken together, the articles ask: How has election reporting evolved over the last century across different media? Has the relationship between journalists and candidates changed in the digital age of campaigning? How do contemporary news values influence campaign coverage? Which voices – politicians, say or journalists – are most prominent? How far do citizens inform election coverage? How is public opinion articulated in the age of social media? Are sites such as Twitter developing new and distinctive election agendas? In what ways does social media interact with legacy media? How well have scholars researched and theorised election reporting cross-nationally? How can research agendas be enhanced? Overall, we argue this Special Issue demonstrates the continued strength of news media during election campaigns. This is in spite of social media platforms increasingly disrupting and recasting the agenda setting power of legacy media, not least by political parties and candidates who are relying more heavily on sites such as Facebook, Instagram and Twitter to campaign. But while debates in recent years have centred on the technological advances in political communication and the associated role of social media platforms during election campaigns (e.g. microtargeting voters, spreading disinformation/misinformation and allowing candidates to bypass media to campaign), our collection of studies signal the enduring influence professional journalists play in selecting and framing of news. Put more simply, how elections are reported still profoundly matters in spite of political parties’ and candidates’ more sophisticated use of digital campaigning.

Big Data and Analytics

2020 ◽  
pp. 47-65
Author(s):  
Sheik Abdullah A. ◽  
Priyadharshini P.
Keyword(s):  
Social Media ◽  
Big Data ◽  
Predictive Analytics ◽  
Data Warehousing ◽  
Big Data Analytics ◽  
Structured Data ◽  
Social Media Analytics ◽  
Data Set ◽  
Data Volume ◽  
Tools And Techniques

The term Big Data corresponds to a large dataset which is available in different forms of occurrence. In recent years, most of the organizations generate vast amounts of data in different forms which makes the context of volume, variety, velocity, and veracity. Big Data on the volume aspect is based on data set maintenance. The data volume goes to processing usual a database but cannot be handled by a traditional database. Big Data is stored among structured, unstructured, and semi-structured data. Big Data is used for programming, data warehousing, computational frameworks, quantitative aptitude and statistics, and business knowledge. Upon considering the analytics in the Big Data sector, predictive analytics and social media analytics are widely used for determining the pattern or trend which is about to happen. This chapter mainly deals with the tools and techniques that corresponds to big data analytics of various applications.

scholarly journals The Vlaams Belang: A Mass Party of the 21st Century

2021 ◽  
Vol 9 (4) ◽  
pp. 275-285 ◽  
Author(s):  
Judith Sijstermans
Keyword(s):  
Decision Making ◽  
Social Media ◽  
Political Parties ◽  
21St Century ◽  
Party System ◽  
Party Organisation ◽  
Important Player ◽  
Social Media Tools ◽  
Party Members ◽  
Local Party

Throughout its 40-year history, the Vlaams Belang (VB, Flemish Interest) has established itself as an important player within the Belgian party system, albeit with significant electoral fluctuations. In 2019, it became the second largest party in Flanders. The party developed and maintained a mass-party organisation by investing significantly in local party branches and in a rigid vertically articulated structure. It relies heavily on social media, particularly Facebook, to communicate to supporters beyond the more limited group of party members. Using both modern and traditional tools, VB representatives aim to create communities of supporters bonded to the party, facilitating dissemination of the party’s messages. Despite this investment in a grassroots organisation, the VB’s decision-making remains highly centralised. Social media and local branches allow informal consideration of members’ views, but the party has not created significant mechanisms for internal democracy. While it is often claimed that political parties have moved away from the “mass-party” model, this article demonstrates that the VB still maintains characteristics of the mass party, albeit with a modern twist. New social media tools facilitate attempts to foster communities and disseminate party messages among a wider group of supporters, both formal members and more informal sympathisers.

The Role of Money in Politics

2020 ◽  
pp. 245-264
Author(s):  
Robert E. Mutch
Keyword(s):  
Public Policy ◽  
Eighteenth Century ◽  
Political Parties ◽  
Government Regulation ◽  
Election Campaigns ◽  
Party Members ◽  
To Come ◽  
Modern Sense ◽  
Money In Politics

Money in some form has always been needed to finance politics, even in the eighteenth century, before there were any political parties or election campaigns in the modern sense. The ways of raising and spending that money have changed many times since then, as have opinions about how it should be raised and spent. As long as that money was raised and spent inside the parties, and as long as it came from politicians themselves and from rank-and-file party members, regulation of campaign funds was minimal. That began to change toward the end of the nineteenth century, when political money began to come from rich donors outside the parties. Government regulation began when opinions about how campaign funds should be raised and spent became legitimate questions of public policy. This chapter reviews how campaign finance practices and the laws regulating them have changed over the course of American history.

Social media penetration, party politics and elections in Tanzania Emerging practices and challenges

2021 ◽  
Vol 20 (1) ◽  
pp. 159-185
Author(s):  
Christopher Simeon Awinia
Keyword(s):  
Social Media ◽  
Political Parties ◽  
Political Party ◽  
Party Politics ◽  
General Elections ◽  
Party Members ◽  
Party Ideology ◽  
Use Of Social Media ◽  
The Way

Tanzania has witnessed an increased use of social media in political party campaigning over the last decade. Use of social media was nonetheless curtailed by a changing techno-political framework regulated by acts relating to cybersecurity and statistics. This study was guided by two hypotheses: firstly, that despite restrictive cybersecurity laws, social media in recent years has been effectively institutionalised as a new civic cyberspace for political party campaigns during elections. Secondly, increasing use of social media in elections has had a transformative effect on the way party structure was organised to conduct political mobilisation, promote party ideology and both inter- and intra-party interaction, and for fundraising. The study interviewed party members and leaders from five political parties which participated in the 2015 and 2020 general elections and concluded that social media had a transformative effect on core political party campaign activities.

Read All About It: The Politicization of “Fake News” on Twitter

2018 ◽  
Vol 95 (2) ◽  
pp. 497-517 ◽  
Author(s):  
John Brummette ◽  
Marcia DiStaso ◽  
Michail Vafeiadis ◽  
Marcus Messner
Keyword(s):  
Social Media ◽  
Cluster Analysis ◽  
Content Analysis ◽  
Social Network ◽  
Political Parties ◽  
Word Choice ◽  
Fake News ◽  
Online Networks ◽  
Party Members ◽  
And Cluster Analysis

Due to the importance of word choice in political discourse, this study explored the use of the term “fake news.” Using a social network analysis, content analysis, and cluster analysis, political characteristics of online networks that formed around discussions of “fake news” were examined. This study found that “fake news” is a politicized term where conversations overshadowed logical and important discussions of the term. Findings also revealed that social media users from opposing political parties communicate in homophilous environments and use “fake news” to disparage the opposition and condemn real information disseminated by the opposition party members.

scholarly journals Performance Analysis of Machine Learning Algorithms for Big Data Classification

2021 ◽  
Vol 12 (4) ◽  
pp. 60-75
Author(s):  
Sanjeev Kumar Punia ◽  
Manoj Kumar ◽  
Thompson Stephan ◽  
Ganesh Gopal Deverajan ◽  
Rizwan Patan
Keyword(s):  
Machine Learning ◽  
Social Media ◽  
Big Data ◽  
Research Data ◽  
Structured Data ◽  
Unstructured Data ◽  
Support Vector ◽  
Classification Algorithms ◽  
Data Set ◽  
Machine Learning Classification

In broad, three machine learning classification algorithms are used to discover correlations, hidden patterns, and other useful information from different data sets known as big data. Today, Twitter, Facebook, Instagram, and many other social media networks are used to collect the unstructured data. The conversion of unstructured data into structured data or meaningful information is a very tedious task. The different machine learning classification algorithms are used to convert unstructured data into structured data. In this paper, the authors first collect the unstructured research data from a frequently used social media network (i.e., Twitter) by using a Twitter application program interface (API) stream. Secondly, they implement different machine classification algorithms (supervised, unsupervised, and reinforcement) like decision trees (DT), neural networks (NN), support vector machines (SVM), naive Bayes (NB), linear regression (LR), and k-nearest neighbor (K-NN) from the collected research data set. The comparison of different machine learning classification algorithms is concluded.

The Political Bases of Citizen Contacting: A Cross-National Analysis

1985 ◽  
Vol 79 (1) ◽  
pp. 117-131 ◽  
Author(s):  
Alan S. Zuckerman ◽  
Darrell M. West
Keyword(s):  
Political Parties ◽  
Political Participation ◽  
Economic Resources ◽  
The Political ◽  
Election Campaigns ◽  
Government Officials ◽  
Data Set ◽  
Political Ties ◽  
National Analysis ◽  
Cross National

This article examines a mode of political participation that frequently has been overlooked—individual efforts to obtain assistance from government officials. Using the seven-nation data set of Verba, Nie, and Kim, we develop and empirically evaluate alternatiave models of citizen contacting. Our first model draws on variations in the distribution of social and economic resources to explain the likelihood of contacting. The second focuses on differences in political ties to locate those most likely to contact government officials. We find greater support for the political ties model. Persons active in political parties and election campaigns are the most likely to engage in citizen contacting. Without political ties, few poor or uneducated persons would ask officials for assistance. We conclude by noting the more general theoretical and normative implications of our study.

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