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The Resource Analyzing Political Communication with Digital Trace Data : The Role of Twitter Messages in Social Science Research

Analyzing Political Communication with Digital Trace Data : The Role of Twitter Messages in Social Science Research

Analyzing Political Communication with Digital Trace Data : The Role of Twitter Messages in Social Science Research
Analyzing Political Communication with Digital Trace Data
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The Role of Twitter Messages in Social Science Research
This book offers a framework for the analysis of political communication in election campaigns based on digital trace data that documents political behavior, interests and opinions. The author investigates the data-generating processes leading users to interact with digital services in politically relevant contexts. These interactions produce digital traces, which in turn can be analyzed to draw inferences on political events or the phenomena that give rise to them. Various factors mediate the image of political reality emerging from digital trace data, such as the users of digital services' political interests, attitudes or attention to politics. In order to arrive at valid inferences about the political reality on the basis of digital trace data, these mediating factors have to be accounted for. The author presents this interpretative framework in a detailed analysis of Twitter messages referring to politics in the context of the 2009 federal elections in Germany. This book will appeal to scholars interested in the field of political communication, as well as practitioners active in the political arena
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Contributions to Political Science Ser
Analyzing Political Communication with Digital Trace Data : The Role of Twitter Messages in Social Science Research
Analyzing Political Communication with Digital Trace Data : The Role of Twitter Messages in Social Science Research
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  • Preface -- Contents -- List of Figures -- List of Tables -- 1 Introduction: How to Use Twitter in the Social Sciences -- 1.1 Digital Trace Data as Information Source for PoliticalPhenomena -- 1.2 A Map of the Territory -- 1.3 Research Goals -- 1.4 Structure of the Book -- References -- 2 Twitter, Usage and Research -- 2.1 Why Twitter? -- 2.2 What is Twitter and How is it Used? -- 2.2.1 What is Twitter? -- 2.2.2 Usage Patterns -- 2.3 Political Uses of Twitter: Politicians, Activists, Citizens, and the Media -- 2.4 Rise to Prominence -- References -- 3 Twitter in the Analysis of Social Phenomena: An Interpretative Framework -- 3.1 Analyzing Social Phenomena with Digital Trace Data -- 3.2 What Are Digital Trace Data? -- 3.3 Computational Social Science, Digital Methods, and Big Data: What Is Missing? -- 3.3.1 Computational Social Science -- 3.3.2 Digital Methods -- 3.3.3 Big Data -- 3.3.4 Why We Need Theory -- 3.4 Twitter: Macro-Phenomena, Micro-Behavior,and Macro-Patterns -- 3.4.1 Approaches to the Analysis of Digital Trace Data -- 3.4.2 Macro-Phenomena, Micro-Behavior, and Macro-Patterns -- 3.4.3 Metrics for the Analysis of Social Phenomena Based on Twitter Data -- 3.4.4 Different Services, Different Uses, Different Data-Generating Processes -- 3.4.5 Politics Through the Lens of Digital Trace Data -- 3.5 A Mechanism Explaining the Publication of Tweets -- 3.5.1 Social Context -- 3.5.2 State of the Twittersphere -- 3.5.3 External Stimuli -- 3.5.4 A Person's Propensity to Tweet -- 3.5.5 What Does This Mechanism Enable Us to Do? -- 3.6 A Framework for the Analysis of Social Phenomena with Twitter Data -- References -- 4 Twitter as Political Communication Space: Publics, Prominent Users, and Politicians -- 4.1 The Political Communication Space -- 4.2 Data Collection and Preparation -- 4.3 Publics -- 4.3.1 Publics: Message-Centric Analysis
  • 4.3.2 Publics: Dynamics Over Time -- 4.3.3 Publics: User-Centric Analysis -- 4.3.4 Publics: Political Support and Opposition -- 4.3.5 Publics: Patterns in the Use of Twitter -- 4.4 Prominent Users -- 4.4.1 Prominent Users: General Observations -- 4.4.2 Prominent Users: Message-Centric Analysis -- 4.4.3 Prominent Users: User-Centric Analysis -- 4.4.4 Prominent Users: Political Support -- 4.4.5 Prominent Users: Patterns in the Use of Twitter -- 4.5 Politicians -- 4.5.1 Politicians: General Observations -- 4.5.2 Politicians: Message-Centric Analysis -- 4.5.3 Politicians: User-Centric Analysis -- 4.5.4 Politicians: Content -- 4.5.5 Politicians: Patterns in the Use of Twitter -- 4.6 Publics, Prominent Users, and Politicians in Their Use of Twitter -- References -- 5 Sensor of Attention to Politics -- 5.1 Connecting Politically Relevant Events to Spikes in the Volume of Twitter Messages -- 5.2 How to Detect Spikes in Data Streams? -- 5.3 Identifying Politically Relevant Events -- 5.4 Political Events and Their Shadows on Twitter -- 5.4.1 Event Detection by Differencing -- 5.4.2 Event Detection by Regression Models -- 5.4.3 Index of Political Relevance -- 5.4.4 Parties -- 5.4.5 Candidates -- 5.4.6 Controversies -- Access Impediment Act -- Ulla Schmidt -- Karl-Theodor zu Guttenberg -- Josef Ackermann -- Kunduz -- Common Patterns: Hashtag Mentions of Controversies -- 5.5 Twitter as a Sensor of Political Attention -- References -- 6 The Media Connection -- 6.1 The Connection Between Political Media Coverage and Twitter Activity -- 6.2 Data Set and Method -- 6.3 Temporal Patterns in the Coverage of Politics on Twitter and Traditional Media -- 6.3.1 Temporal Dynamics -- 6.3.2 Common Patterns in the Mentions of Political Actors Across Media Types -- 6.4 What Do Users Tweet About in Reaction to Mediated Events?
  • 6.4.1 Ratification of the Access Impediment Act: Temporal Dynamics and Content -- 6.4.2 State Elections: Temporal Dynamics and Content -- 6.4.3 Televised Leaders' Debate: Temporal Dynamicsand Content -- 6.4.4 Election Day: Temporal Dynamics and Content -- 6.5 Twitter and Political Coverage by Traditional Media -- References -- 7 Predictor of Electoral Success and Public Opinion at Large -- 7.1 The Connection Between Attention on Twitter and Electoral Fortunes -- 7.2 Predicting Election Results Using Twitter Data: The Evidence -- 7.3 Mechanisms Linking Twitter Messages with Opinion Polls and Election Results -- 7.4 Method -- 7.5 Twitter Metrics and Their Relationship to the Electoral Fortunes of Parties -- 7.5.1 Aggregates, Twitter Metrics: Users, Mentionsand Sentiment -- 7.5.2 Dynamics of Hashtag Mentions Compared to Shifts in Opinion Polls -- 7.6 No Indicator of Political Support or Public Opinion at Large -- References -- 8 Conclusion: Twitter and the Analysis of Social Phenomena -- 8.1 Early Days -- 8.2 Characteristics of Twitter as a Political Communication Space -- 8.3 A Framework for the Use of Twitter in the Analysis of Social Phenomena -- 8.4 Twitter: Political Communication Space and Mediator of Politics -- References
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