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A hands on guide to web scraping and text mining for both beginners and experienced users of R
Introduces fundamental concepts of the main architecture of the web and databases and covers HTTP, HTML, XML, JSON, SQL.
Provides basic techniques to query web documents and data sets (XPath and regular expressions).
An extensive set of exercises are presented to guide the reader through each technique.
Explores both supervised and unsupervised techniques as well as advanced techniques such as data scraping and text management.
Case studies are featured throughout along with examples for each technique presented.
R code and solutions to exercises featured in the book are provided on a supporting website.
Forecasting Elections in Multiparty Systems: A Bayesian Approach Combining Polls and Fundamentals
(2019)
We offer a dynamic Bayesian forecasting model for multiparty elections. It combines data from published pre-election public opinion polls with information from fundamentals-based forecasting models. The model takes care of the multiparty nature of the setting and allows making statements about the probability of other quantities of interest, such as the probability of a plurality of votes for a party or the majority for certain coalitions in parliament. We present results from two ex ante forecasts of elections that took place in 2017 and are able to show that the model outperforms fundamentals-based forecasting models in terms of accuracy and the calibration of uncertainty. Provided that historical and current polling data are available, the model can be applied to any multiparty setting.
Hitler’s rise to power amidst an unprecedented propaganda campaign initiated scholarly interest in campaign effects. To the surprise of many, empirical studies often found minimal effects. The predominant focus of early work was on U.S. elections, though. Nazi propaganda as the archetypal and, in many ways, most likely case for strong effects has rarely been studied. We collect extensive data about Hitler’s speeches and gauge their impact on voter support at five national elections preceding the dictatorship. We use a semi-parametric difference-in-differences approach to estimate effects in the face of potential confounding due to the deliberate scheduling of events. Our findings suggest that Hitler’s speeches, while rationally targeted, had a negligible impact on the Nazis’ electoral fortunes. Only the 1932 presidential runoff, an election preceded by an extraordinarily short, intense, and one-sided campaign, yielded positive effects. This study questions the importance of charismatic leaders for the success of populist movements.
We point to a popular yet underresearched platform of political information, the online encyclopedia Wikipedia. Considering the supply side of the marketplace, we argue that personal biographies on the platform are an attractive medium for politicians to enhance their appearance. We trace changes to biographies coming from the parliament using data that cover the entire edit histories for biographies on all German members of parliament for the three last legislative periods. Our findings show editing of personal biographies to be a persistent phenomenon. Moreover, type, timing, and driving factors of editing behavior highlight the importance politicians’ attribute to Wikipedia for pursuing reelection. Our results speak to the domains of political professionalization, voting behavior, and the general measurement of communicative patterns.
Estimating Constituency Preferences from Sparse Survey Data Using Auxiliary Geographic Information
(2011)
Measures of constituency preferences are of vital importance for the study of political representation and other research areas. Yet, such measures are often difficult to obtain. Previous survey-based estimates frequently lack precision and coverage due to small samples, rely on questionable assumptions or require detailed auxiliary information about the constituencies' population characteristics. We propose an alternative Bayesian hierarchical approach that exploits minimal geographic information readily available from digitalized constituency maps. If at hand, social background data are easily integrated. To validate the method, we use national polls and district-level results from the 2009 German Bundestag election, an empirical case for which detailed structural information is missing.
Das Kapitel bietet einen Überblick der Webdatensammlung für die sozialwissenschaftliche Forschung. Zu diesem Zweck wird nach einem praktischen Beispiel eine Übersicht der grundlegenden Webtechnologien geboten, um in einem zweiten Schritt einen vertiefenden Blick auf das Web Scraping einerseits und Programmierschnittstellen andererseits zu werfen. Die praktische Umsetzung der Webdatensammlung wird mit Code-Beispielen in der Programmiersprache R illustriert. Nach der praktischen Einführung werden Potenziale und Herausforderungen der webbasierten Sozialwissenschaft am Beispiel ausgewählter Anwendungen aus der aktuellen Forschungsliteratur diskutiert. Abschließend werden verschiedene technische und konzeptionelle Problemstellungen der Webdatensammlung dargelegt und einige weiterführende Literaturhinweise für die vertiefte Auseinandersetzung mit den Themen des Kapitels geboten.
Bei der Entwicklung der räumlichen Modelle des Parteienwettbewerbs spielt die Valenz eine wichtige Rolle. Trotz der theoretischen Relevanz bleibt die Mess- und Schätzmethode der Valenz unterentwickelt. Angesichts dieser Forschungslücke schlägt dieser Beitrag ein statistisches Modell vor, das die gleichzeitige Schätzung der Kandidatenpositionen und der Valenz ermöglicht. Ein wichtiger Vorzug dieses Modells liegt darin, dass man nur die Kandidatenbeurteilungen per Skalometer benötigt, der in den meisten Umfragedaten verfügbar ist. Dieses Modell wird auf Daten angewendet, die in Rahmen der Konstanzer Oberbürgermeisterwahl 2012 erhoben wurden.
