Analyzing audiovisual communication is challenging because its content is highly symbolic and less rule-governed than verbal material. But audiovisual messages are important to understand: they amplify, enrich, or complicate the content of textual information. To address these measurement challenges, we describe a fully reproducible approach to analyzing video content using minimally – but systematically – trained online workers. By aggregating the work of multiple coders, the online approach achieves reliability, validity, and costs that equal those of traditional, intensively trained research assistants, with much greater speed, transparency, and replicability. We argue that measurement strategies relying on the “wisdom of the crowd” prov...
Between 2012 and 2016, generous funding by the Austrian Science Fund allowed me to conduct a researc...
Political scientists lack domain-specific measures for the purpose of measuring the sophistication o...
Data and code to replicate findings in "Text Preprocessing For Unsupervised Learning: Why It Matters...
Empirical social science often relies on data that are not observed in the field, but are coded into...
Audio-visual data is ubiquitous in politics. Campaign advertisements, political debates, and the new...
Replication Materials (Data and Code) for 'Text as Data' Abstract: Politics and political conflict o...
Much of the data used in Political Science is extracted from news reports. This is typically accompl...
The Internet, as a digital record of human discourse, provides an opportunity to directly analyze po...
Crowd‐coding is a novel technique that allows for fast, affordable and reproducible online categoris...
In the digital age, in a time where increasing amounts of video are being published and distributed ...
Self-reported measures of media exposure are plagued with error and questions about validity. Since ...
The dataset is first introduced in the following paper: Siqi Wu, Marian-Andrei Rizoiu, and Lexing...
Abstract: Renewed efforts at empirically distinguishing between different forms of political regimes...
Data and code to replicate findings in "Liberals Lecture, Conservatives Communicate: analyzing compl...
Empirical social science often relies on data that are not observed in the field, but are transforme...
Between 2012 and 2016, generous funding by the Austrian Science Fund allowed me to conduct a researc...
Political scientists lack domain-specific measures for the purpose of measuring the sophistication o...
Data and code to replicate findings in "Text Preprocessing For Unsupervised Learning: Why It Matters...
Empirical social science often relies on data that are not observed in the field, but are coded into...
Audio-visual data is ubiquitous in politics. Campaign advertisements, political debates, and the new...
Replication Materials (Data and Code) for 'Text as Data' Abstract: Politics and political conflict o...
Much of the data used in Political Science is extracted from news reports. This is typically accompl...
The Internet, as a digital record of human discourse, provides an opportunity to directly analyze po...
Crowd‐coding is a novel technique that allows for fast, affordable and reproducible online categoris...
In the digital age, in a time where increasing amounts of video are being published and distributed ...
Self-reported measures of media exposure are plagued with error and questions about validity. Since ...
The dataset is first introduced in the following paper: Siqi Wu, Marian-Andrei Rizoiu, and Lexing...
Abstract: Renewed efforts at empirically distinguishing between different forms of political regimes...
Data and code to replicate findings in "Liberals Lecture, Conservatives Communicate: analyzing compl...
Empirical social science often relies on data that are not observed in the field, but are transforme...
Between 2012 and 2016, generous funding by the Austrian Science Fund allowed me to conduct a researc...
Political scientists lack domain-specific measures for the purpose of measuring the sophistication o...
Data and code to replicate findings in "Text Preprocessing For Unsupervised Learning: Why It Matters...