scholarly journals Friends With Text as Data Benefits: Assessing and Extending the Use of Automated Text Analysis in Political Science and Political Psychology

2017 ◽  
Author(s):  
Martijn Schoonvelde ◽  
Gijs Schumacher ◽  
Bert Bakker
Keyword(s):  
Political Psychology ◽  
Political Science ◽  
Text Analysis ◽  
Research Process ◽  
Critical Discussion ◽  
Unstructured Data ◽  
Policy Positions ◽  
Disciplinary Boundaries ◽  
Automated Text Analysis ◽  
Key Issues

Applications of automated text analysis measuring topics, ideology, sentiment or even personality are booming in fields like political science and political psychology. These developments are to be applauded as they bring about novel insights about politics using new sources of (unstructured) data. However, a divide exists between work in both disciplines using text as data. In this paper we argue in favor of more integration across disciplinary boundaries, structuring our case around four key issues in the research process: (i) sampling text; (ii) authorship as meta data; (iii) pre- processing text; (iv) analyzing text. Along the way we demonstrate that an assessment of speaker characteristics may crucially depend on the text sources under study, and that the use of senti- ment words correlates with estimates of policy positions, with implications for interpretation of the latter. As such, this paper contributes to a critical discussion about the merits of automated text analysis methods in political psychology and political science, with an eye towards advancing the considerable potential of text as data in the study of politics.

scholarly journals Friends with text as data benefits: Assessing and extending the use of automated text analysis in political science and political psychology

2019 ◽  
Vol 7 (1) ◽  
pp. 124-143 ◽  
Author(s):  
Martijn Schoonvelde ◽  
Gijs Schumacher ◽  
Bert N. Bakker
Keyword(s):  
Political Psychology ◽  
Political Science ◽  
Text Analysis ◽  
Research Process ◽  
Critical Discussion ◽  
Unstructured Data ◽  
Policy Positions ◽  
Disciplinary Boundaries ◽  
Automated Text Analysis ◽  
Key Issues

Applications of automated text analysis measuring topics, ideology, sentiment or even personality are booming in fields like political science and political psychology. These developments are to be applauded as they bring about novel insights about politics using new sources of (unstructured) data. However, a divide exists between work in both disciplines using text as data. In this paper we argue in favor of more integration across disciplinary boundaries, structuring our case around four key issues in the research process: (i) sampling text; (ii) authorship as meta data; (iii) pre-processing text; (iv) analyzing text. Along the way we demonstrate that an assessment of speaker characteristics may crucially depend on the text sources under study, and that the use of sentiment words correlates with estimates of policy positions, with implications for interpretation of the latter. As such, this paper contributes to a critical discussion about the merits of automated text analysis methods in political psychology and political science, with an eye towards advancing the considerable potential of text as data in the study of politics.

scholarly journals Text as Data in Political Psychology

2019 ◽  
Author(s):  
Martijn Schoonvelde ◽  
Christian Pipal ◽  
Gijs Schumacher
Keyword(s):  
Natural Language ◽  
Political Psychology ◽  
Political Science ◽  
Text Analysis ◽  
Current State ◽  
Analysis Methods ◽  
Automated Text Analysis ◽  
Core Questions ◽  
State Of Affairs

This chapter provides an assessment of automated text analysis methods in political psychology structured around the following core questions: (i) What is the current state of affairs of text as data in political psychology? (ii) What can political science and politicalpsychology learn from each other when it comes to analysing natural language? (iii) Wheredoes text as data in political psychology go next?

scholarly journals Analyzing Text Complexity in Political Science Research

2014 ◽  
Vol 47 (03) ◽  
pp. 663-666 ◽  
Author(s):  
Damon M. Cann ◽  
Greg Goelzhauser ◽  
Kaylee Johnson
Keyword(s):  
Political Science ◽  
Text Analysis ◽  
Science Research ◽  
Text Complexity ◽  
Automated Text Analysis ◽  
Science Article

ABSTRACTThis article analyzes the text complexity of political science research. Using automated text analysis, we examine the text complexity of a sample of articles from three leading generalist journals and four leading subfield journals. We also examine changes in text complexity across time by analyzing a sample of articles from the discipline’s flagship journal during a 100-year span. Although it is not surprising that a typical political science article is difficult to read, it is accessible to intelligent lay readers. We found little difference in text complexity across time or subfield.

China's Newsmakers: Official Media Coverage and Political Shifts in the Xi Jinping Era

2017 ◽  
Vol 233 ◽  
pp. 111-136 ◽  
Author(s):  
Kyle Jaros ◽  
Jennifer Pan
Keyword(s):  
Text Analysis ◽  
Media Coverage ◽  
Past Research ◽  
Early Years ◽  
Xi Jinping ◽  
Political Actors ◽  
Party Organizations ◽  
Automated Text Analysis ◽  
The Media ◽  
Party Dominance

AbstractXi Jinping's rise to power in late 2012 brought immediate political realignments in China, but the extent of these shifts has remained unclear. In this paper, we evaluate whether the perceived changes associated with Xi Jinping's ascent – increased personalization of power, centralization of authority, Party dominance and anti-Western sentiment – were reflected in the content of provincial-level official media. As past research makes clear, media in China have strong signalling functions, and media coverage patterns can reveal which actors are up and down in politics. Applying innovations in automated text analysis to nearly two million newspaper articles published between 2011 and 2014, we identify and tabulate the individuals and organizations appearing in official media coverage in order to help characterize political shifts in the early years of Xi Jinping's leadership. We find substantively mixed and regionally varied trends in the media coverage of political actors, qualifying the prevailing picture of China's “new normal.” Provincial media coverage reflects increases in the personalization and centralization of political authority, but we find a drop in the media profile of Party organizations and see uneven declines in the media profile of foreign actors. More generally, we highlight marked variation across provinces in coverage trends.

Automated Text Analysis: Cautionary Tales

1994 ◽  
Vol 9 (4) ◽  
pp. 295-302 ◽  
Author(s):  
C. N. BALL
Keyword(s):  
Text Analysis ◽  
Automated Text Analysis ◽  
Cautionary Tales

scholarly journals Research and practice

2014 ◽  
Vol 70 (6) ◽  
pp. 1039-1053 ◽  
Author(s):  
Mark Hepworth ◽  
Philipp Grunewald ◽  
Geoff Walton
Keyword(s):  
Phenomenological Approach ◽  
Critical Discussion ◽  
Research Literature ◽  
Research Experience ◽  
Content Type ◽  
Information Behaviour ◽  
Relative Value ◽  
Participative Approach ◽  
Key Issues ◽  
Participative Design

Purpose – The purpose of this paper is to provide a critical discussion on the nature of research into people's information behaviour, and in particular the contribution of the phenomenological approach for the development of information solutions. Design/methodology/approach – The approach takes the form of a conceptual analysis drawing on the research literature and personal research experience. Findings – The paper brings to the foreground the relative value of different conceptual approaches and how these underpin and relate to the development of information solutions. Research limitations/implications – The paper, due to the breadth and complexity of the subject, serves to highlight key issues and bringing together ideas. Some topics deserve further explanation. However, this was beyond the scope of this paper. Practical implications – A conceptual framework is provided that indicates the value of the epistemic spectrum for information behaviour studies and provides support for action research and participative design. Social implications – Taking a phenomenological approach, and consequently either a first person approach and/or a highly participative approach to research, challenges the relationship between researcher and respondent. It also raises questions about why the authors conduct research and for whom it is intended. Originality/value – The paper makes explicit the underlying philosophical assumptions and how these ideas influence the way the authors conduct research; it highlights the significance of Cartesian dualism and indicates the significance of these assumptions for the development of information solutions. It supports the view that researchers and developers should be open to respondents leading the exploration of their needs.

Summaries

2018 ◽  
Vol 46 (1) ◽  
Keyword(s):  
Machine Learning ◽  
Content Analysis ◽  
Text Analysis ◽  
English Language ◽  
Automated Analysis ◽  
Supervised Machine Learning ◽  
Automated Text Analysis ◽  
Research Problems ◽  
Dutch Language ◽  
Automated Methods

Damian Trilling & Jelle Boumans Automated analysis of Dutch language-based texts. An overview and research agenda While automated methods of content analysis are increasingly popular in today’s communication research, these methods have hardly been adopted by communication scholars studying texts in Dutch. This essay offers an overview of the possibilities and current limitations of automated text analysis approaches in the context of the Dutch language. Particularly in dictionary-based approaches, research is far less prolific as research on the English language. We divide the most common types of content-analytical research questions into three categories: 1) research problems for which automated methods ought to be used, 2) research problems for which automated methods could be used, and 3) research problems for which automated methods (currently) cannot be used. Finally, we give suggestions for the advancement of automated text analysis approaches for Dutch texts. Keywords: automated content analysis, Dutch, dictionaries, supervised machine learning, unsupervised machine learning

scholarly journals Let’s do better: public representations of COVID-19 science

FACETS ◽  
2021 ◽  
Vol 6 (1) ◽  
pp. 403-423
Author(s):  
Timothy Caulfield ◽  
Tania Bubela ◽  
Jonathan Kimmelman ◽  
Vardit Ravitsky
Keyword(s):  
Biomedical Research ◽  
Public Trust ◽  
Research Process ◽  
Research Community ◽  
Public Communication ◽  
The Public ◽  
Research Communities ◽  
Key Issues ◽  
Bad Data

COVID science is being both done and circulated at a furious pace. While it is inspiring to see the research community responding so vigorously to the pandemic crisis, all this activity has also created a churning sea of bad data, conflicting results, and exaggerated headlines. With representations of science becoming increasingly polarized, twisted, and hyped, there is growing concern that the relevant science is being represented to the public in a manner that may cause confusion, inappropriate expectations, and the erosion of public trust. Here we explore some of the key issues associated with the representations of science in the context of the COVID-19 pandemic. Many of these issues are not new. But the COVID-19 pandemic has placed a spotlight on the biomedical research process and amplified the adverse ramifications of poor public communication. We need to do better. As such, we conclude with 10 recommendations aimed at key actors involved in the communication of COVID-19 science, including government, funders, universities, publishers, media, and the research communities.

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