74 research outputs found
Text analysis in R
Computational text analysis has become an exciting research field with many applications in communication research. It can be a difficult method to apply, however, because it requires knowledge of various techniques, and the software required to perform most of these techniques is not readily available in common statistical software packages. In this teacher’s corner, we address these barriers by providing an overview of general steps and operations in a computational text analysis project, and demonstrate how each step can be performed using the R statistical software. As a popular open-source platform, R has an extensive user community that develops and maintains a wide range of text analysis packages. We show that these packages make it easy to perform advanced text analytics
RTextTools: A Supervised Learning Package for Text Classification
Social scientists have long hand-labeled texts to create datasets useful for studying topics
from congressional policymaking to media reporting. Many social scientists have begun to incorporate
machine learning into their toolkits. RTextTools was designed to make machine learning accessible
by providing a start-to-finish product in less than 10 steps. After installing RTextTools, the initial
step is to generate a document term matrix. Second, a container object is created, which holds all
the objects needed for further analysis. Third, users can use up to nine algorithms to train their data.
Fourth, the data are classified. Fifth, the classification is summarized. Sixth, functions are available for
performance evaluation. Seventh, ensemble agreement is conducted. Eighth, users can cross-validate
their data. Finally, users write their data to a spreadsheet, allowing for further manual coding if
required
Diverse politics, diverse news coverage? A longitudinal study of diversity in Dutch political news during two decades of election campaigns
Although diverse political news has been recognized as a requirement for a well-functioning democracy, longitudinal research into this topic is sparse. In this article, we analyse the development of diversity in election coverage in the Netherlands between 1994 and 2012. We distinguish between diversity for party and issue coverage, and look at differences between diversity in newspapers and television news. Results show that news diversity varies over time. Diversity for party types increased over time. We found no clear trend for diversity of issue dimensions. Compared to newspapers, television news is more diverse for party types but less diverse on issue dimensions. The question concerning whether these findings are an indicator of structural bias is discussed
Linking event archives to news: a computational method for analyzing the gatekeeping process
Digital archives that document real-world events provide new opportunities for large-scale analyses of how news coverage represents reality. We present a method and open-source tool for linking event data to news articles, and demonstrate its application with an analysis of event and country level predictors of terrorism coverage in The Guardian from 2006 to 2018, using event data from the Global Terrorism Database (GTD). Our method builds on established techniques for calculating document similarity, and we propose a novel strategy for fine-tuning parameters of the event matching algorithm that requires no manual coding. An online appendix is provided that documents all code to replicate our analysis and reuse our tools
Multiperspectival normative assessment: The case of mediated reactions to terrorism
This article provides a model for how communication phenomena can be normatively
assessed using multiple normative perspectives simultaneously. We exemplify the proce-
dure of multiperspectival normative assessment (MNA) using mediated reactions to ter-
rorism as our case in point. We first identify the normative challenges related to the
speed and substance of terrorism communication and the ways in which relations of
solidarity are communicatively constructed in reacting to terrorism. We link these chal-
lenges to four distinct normative theories that prioritize competing values for public dis-
course (freedom, community values, empowerment of the marginalized or constructive
debate). The resulting set of competing normative expectations, which help assess the
performance of terrorism communication, are eventually translated into recommenda-
tions for professional and non-professional communicators. In conclusion, we show
how MNA can help ground empirical scholarship in firmer theoretical foundations
while simultaneously demonstrating the usefulness of normative theory in analyzing a
wide range of issues
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Computational Communication Science: A Methodological Catalyzer for a Maturing Discipline
Topic Modeling and Text Analysis for Qualitative Policy Research
This paper contributes to a critical methodological discussion that has direct ramifications for policy studies: how computational methods can be concretely incorporated into existing processes of textual analysis and interpretation without compromising scientific integrity. We focus on the computational method of topic modeling and investigate how it interacts with two larger families of qualitative methods: content and classification methods characterized by interest in words as communication units and discourse and representation methods characterized by interest in the meaning of communicative acts. Based on analysis of recent academic publications that have used topic modeling for textual analysis, our findings show that different mixed‐method research designs are appropriate when combining topic modeling with the two groups of methods. Our main concluding argument is that topic modeling enables scholars to apply policy theories and concepts to much larger sets of data. That said, the use of computational methods requires genuine understanding of these techniques to obtain substantially meaningful results. We encourage policy scholars to reflect carefully on methodological issues, and offer a simple heuristic to help identify and address critical points when designing a study using topic modeling.Peer reviewe
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