Political methodology

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Political methodology is a subfield of political science that studies the quantitative and qualitative methods used to study politics and draw conclusions using data. Quantitative methods combine statistics, mathematics, and formal theory. Political methodology is often used for positive research, in contrast to normative research. Psephology, a skill or technique within political methodology, is the "quantitative analysis of elections and balloting". [1]

Contents

Objective political research heavily relies on political methodology as it provides rigorous methods for analysis. Quantitative methods, including statistical analysis, can allow researchers to investigate large datasets and identify patterns or trends, such as to predict election outcomes. Oppositely, qualitative methods deal with deep analysis of smaller sets of data such as interviews, documents, and case studies. This methods of analysis are more specifically useful when it comes to analyzing complicated social phenomena and political behavior. By combining these two types of methods, researchers can get a more comprehensive understanding of political processes and outcomes [2] .

History of Political Methodology

Pre 2000s Development

The first steps toward developing quantitative analysis date back to the 1880s, where the first statistics course was offered at Columbia University, setting the stage for combining quantitative perspectives into politics. Then, in 1919, the first political science journal utilizing quantitative methods was published, which helped grow the development of the field. [3] This led to the first major phase in the 1920s, where scholars such as Charles Merriam showcased the importance of incorporating statistics into various forms of analysis. Political scientists would gather diverse data, including election statistics and campaign data, in order to take the study away from simple observation and involve deep numerical input. [3]

The second phase came about in the late 1960s with the behavioral revolution, which is characterized by the large increase in quantitative methods. By this time, over fifty percent of the American Political Science Review (ASPR) articles used these methods. In the 1970s, there was a shift towards creating original sets of data to measure specific abstract political concepts such as ideology and representation. [3] Researchers and scholars used innovative approaches including content analysis and event counts to widen the analytical capabilities and answer previous unanswerable questions. A major development that occurred during this period was the use of advanced statistical methods from other fields, such as regression models, time series analysis, and scaling techniques. These methods, however, needed various adjustments and adaptations in order to better suite the field of political science. [3] Development followed in the next couple of decades, notably with the addition of computational methods in the late 1980s onward. New methods using advance technology were used to perform much larger and impressive tasks such as simulation and advanced econometrics. [4]

Big Data Usage

Since comparative politics is a relatively new field in the political science field, there are new trends that emerge within the subfield of political methodology. One of these new trends is the use of "Big Data". Political campaigns and political parties use complex datasets to try to push their agendas and make a better more personalized appeal towards their voter base. [5] Usually, the origin of this data is from surveys and provided information from the voters themselves, but there are instances where these campaigns get their data from cookies or from purchasing the personal data collected by social media sites with the use of "layering data points". [6]

The role that big data plays in the political process isn't fully understood yet since most political campaigns-especially in America- just now started to realize the power of social media [7] , and putting effort into their own socials to target a younger audience. However, The quantitative nature of big data and how the internet influences politics in today's political atmosphere is where we can see the overlap between big data and its use in political methodology more clearly. [7]

Machine Learning

Another big leap in political research techniques within political methodology is machine learning. [8] Machine learning has become an increasingly interesting topic in other fields such as computer science, and even in the medical field. [9] However, the field of political science has also been affected by this phenomenon. [8] Most of those data sets that political campaigns use need to be sorted through, or applied to statistics in order to achieve accurate outcomes and forecasts for probabilities based on the datasets that were stored within the database. [8] Machine learning also allows political scientists to test theories that are derived from the data, and can be put to use in their research methods. This process can narrow down the possibilities of outcomes using both hard data (quantitative) and soft data (qualitative) in simulated scenarios during the research process. [8]

The use of Artificial Intelligence or AI is also a big component of political methodology and is becoming a huge tool for political scientists. Furthermore, more younger students use AI for a myriad of different things at an increasingly high rate already. [10]

Since AI is being used increasingly in research and data collecting, there are some political scientists and researchers who want to find ways to increase civic engagement and information access through the use of AI. [11]

AI Ethics in Political Methodology

There have been political analysts and pollsters that usually rely on empirical methods and statistical models in order to predict the outcome of elections, and other political scenarios. [12] AI has already been used in political ads on a small scale, and in the US, there is not currently any rules against AI developing political ads or advertising material for political campaigns. [12]

As mentioned before, AI mainly uses databases gathered from different methods to predict outcomes. However, at times these outcomes and as well as the way in which the data was used or stored can raise ethical concerns. [13] Similar to how people react to other electronic devices "listening in" on them, people raise similar concerns with AI in regards to political data or personal data that identifies voters' preferences or concerns and is used by candidates for polling data. This aspect of AI transforms political research, but fails to account for the underlying biases, assumptions or privacy concerns associated with AI use in general. [13]

Political Methodology and Public Policy

Evidence-Based Decision Making

Since political methodology is heavily based in quantitative analysis [1] political candidates tend to use these data figures to "play politics" with the opposing side, and to draw their own conclusions using this evidence. [14] Furthermore, political researchers will often work hand in hand with political candidates or office holders to provide real-world examples as a framework for political candidates to base their policy proposals off of. [15]

Politicians often use rhetoric that is believed to be supported by a factual basis, but often times the specific data or analysis that the candidates are referencing has been taken out of context in some regard. [16]

Journals

Political methodology is often published in the "top 3" journals (American Political Science Review, American Journal of Political Science, and Journal of Politics), in sub-field journals, and in methods-focused journals.

Notable researchers

Related Research Articles

<span class="mw-page-title-main">Research</span> Systematic study undertaken to increase knowledge

Research is "creative and systematic work undertaken to increase the stock of knowledge". It involves the collection, organization, and analysis of evidence to increase understanding of a topic, characterized by a particular attentiveness to controlling sources of bias and error. These activities are characterized by accounting and controlling for biases. A research project may be an expansion of past work in the field. To test the validity of instruments, procedures, or experiments, research may replicate elements of prior projects or the project as a whole.

<span class="mw-page-title-main">Social science</span> Branch of science that studies society and its relationships

Social science is one of the branches of science, devoted to the study of societies and the relationships among members within those societies. The term was formerly used to refer to the field of sociology, the original "science of society", established in the 18th century. In addition to sociology, it now encompasses a wide array of academic disciplines, including anthropology, archaeology, economics, geography, linguistics, management, communication studies, psychology, culturology and political science.

Qualitative marketing research involves a natural or observational examination of the philosophies that govern consumer behavior. The direction and framework of the research is often revised as new information is gained, allowing the researcher to evaluate issues and subjects in an in-depth manner. The quality of the research produced is heavily dependent on the skills of the researcher and is influenced by researcher bias.

A case study is an in-depth, detailed examination of a particular case within a real-world context. For example, case studies in medicine may focus on an individual patient or ailment; case studies in business might cover a particular firm's strategy or a broader market; similarly, case studies in politics can range from a narrow happening over time like the operations of a specific political campaign, to an enormous undertaking like world war, or more often the policy analysis of real-world problems affecting multiple stakeholders.

<span class="mw-page-title-main">Multimethodology</span>

Multimethodology or multimethod research includes the use of more than one method of data collection or research in a research study or set of related studies. Mixed methods research is more specific in that it includes the mixing of qualitative and quantitative data, methods, methodologies, and/or paradigms in a research study or set of related studies. One could argue that mixed methods research is a special case of multimethod research. Another applicable, but less often used label, for multi or mixed research is methodological pluralism. All of these approaches to professional and academic research emphasize that monomethod research can be improved through the use of multiple data sources, methods, research methodologies, perspectives, standpoints, and paradigms.

<span class="mw-page-title-main">Qualitative research</span> Form of research

Qualitative research is a type of research that aims to gather and analyse non-numerical (descriptive) data in order to gain an understanding of individuals' social reality, including understanding their attitudes, beliefs, and motivation. This type of research typically involves in-depth interviews, focus groups, or field observations in order to collect data that is rich in detail and context. Qualitative research is often used to explore complex phenomena or to gain insight into people's experiences and perspectives on a particular topic. It is particularly useful when researchers want to understand the meaning that people attach to their experiences or when they want to uncover the underlying reasons for people's behavior. Qualitative methods include ethnography, grounded theory, discourse analysis, and interpretative phenomenological analysis. Qualitative research methods have been used in sociology, anthropology, political science, psychology, communication studies, social work, folklore, educational research, information science and software engineering research.

<span class="mw-page-title-main">Quantitative research</span> All procedures for the numerical representation of empirical facts

Quantitative research is a research strategy that focuses on quantifying the collection and analysis of data. It is formed from a deductive approach where emphasis is placed on the testing of theory, shaped by empiricist and positivist philosophies.

Educational research refers to the systematic collection and analysis of evidence and data related to the field of education. Research may involve a variety of methods and various aspects of education including student learning, interaction, teaching methods, teacher training, and classroom dynamics.

<span class="mw-page-title-main">Content analysis</span> Research method for studying documents and communication artifacts

Content analysis is the study of documents and communication artifacts, which might be texts of various formats, pictures, audio or video. Social scientists use content analysis to examine patterns in communication in a replicable and systematic manner. One of the key advantages of using content analysis to analyse social phenomena is their non-invasive nature, in contrast to simulating social experiences or collecting survey answers.

<span class="mw-page-title-main">Methodology</span> Study of research methods

In its most common sense, methodology is the study of research methods. However, the term can also refer to the methods themselves or to the philosophical discussion of associated background assumptions. A method is a structured procedure for bringing about a certain goal, like acquiring knowledge or verifying knowledge claims. This normally involves various steps, like choosing a sample, collecting data from this sample, and interpreting the data. The study of methods concerns a detailed description and analysis of these processes. It includes evaluative aspects by comparing different methods. This way, it is assessed what advantages and disadvantages they have and for what research goals they may be used. These descriptions and evaluations depend on philosophical background assumptions. Examples are how to conceptualize the studied phenomena and what constitutes evidence for or against them. When understood in the widest sense, methodology also includes the discussion of these more abstract issues.

<span class="mw-page-title-main">Grounded theory</span> Qualitative research methodology

Grounded theory is a systematic methodology that has been largely applied to qualitative research conducted by social scientists. The methodology involves the construction of hypotheses and theories through the collecting and analysis of data. Grounded theory involves the application of inductive reasoning. The methodology contrasts with the hypothetico-deductive model used in traditional scientific research.

<span class="mw-page-title-main">Comparative politics</span> Field in political science

Comparative Politics is a field in Political Science characterized either by the use of the comparative method or other empirical methods to explore politics both within and between countries. Substantively, this can include questions relating to political institutions, political behavior, conflict, and the causes and consequences of economic development. When applied to specific fields of study, Comparative Politics may be referred to by other names, such as comparative government.

Evidence-based policy is a concept in public policy that advocates for policy decisions to be grounded on, or influenced by, rigorously established objective evidence. This concept presents a stark contrast to policymaking predicated on ideology, 'common sense', anecdotes, or personal intuitions. The methodology employed in evidence-based policy often includes comprehensive research methods such as randomized controlled trials (RCT). Good data, analytical skills, and political support to the use of scientific information are typically seen as the crucial elements of an evidence-based approach.

<span class="mw-page-title-main">Systematic review</span> Comprehensive review of research literature using systematic methods

A systematic review is a scholarly synthesis of the evidence on a clearly presented topic using critical methods to identify, define and assess research on the topic. A systematic review extracts and interprets data from published studies on the topic, then analyzes, describes, critically appraises and summarizes interpretations into a refined evidence-based conclusion. For example, a systematic review of randomized controlled trials is a way of summarizing and implementing evidence-based medicine.

David Collier is an American political scientist specializing in comparative politics. He is Chancellor's Professor Emeritus at the University of California, Berkeley. He works in the fields of comparative politics, Latin American politics, and methodology. His father was the anthropologist Donald Collier.

Process tracing is a qualitative research method used to develop and test theories. Process-tracing can be defined as the following: it is the systematic examination of diagnostic evidence selected and analyzed in light of research questions and hypotheses posed by the investigator. Process-tracing thus focuses on (complex) causal relationships between the independent variable(s) and the outcome of the dependent variable(s), evaluates pre-existing hypotheses and discovers new ones. It is generally understood as a "within-case" method to draw inferences on the basis of causal mechanisms, but it can also be used for ideographic research or small-N case-studies. It has been used in social sciences, as well as in natural sciences.

Causal inference is the process of determining the independent, actual effect of a particular phenomenon that is a component of a larger system. The main difference between causal inference and inference of association is that causal inference analyzes the response of an effect variable when a cause of the effect variable is changed. The study of why things occur is called etiology, and can be described using the language of scientific causal notation. Causal inference is said to provide the evidence of causality theorized by causal reasoning.

Thematic analysis is one of the most common forms of analysis within qualitative research. It emphasizes identifying, analysing and interpreting patterns of meaning within qualitative data. Thematic analysis is often understood as a method or technique in contrast to most other qualitative analytic approaches – such as grounded theory, discourse analysis, narrative analysis and interpretative phenomenological analysis – which can be described as methodologies or theoretically informed frameworks for research. Thematic analysis is best thought of as an umbrella term for a variety of different approaches, rather than a singular method. Different versions of thematic analysis are underpinned by different philosophical and conceptual assumptions and are divergent in terms of procedure. Leading thematic analysis proponents, psychologists Virginia Braun and Victoria Clarke distinguish between three main types of thematic analysis: coding reliability approaches, code book approaches and reflexive approaches. They first described their own widely used approach in 2006 in the journal Qualitative Research in Psychology as reflexive thematic analysis. This paper has over 120,000 Google Scholar citations and according to Google Scholar is the most cited academic paper published in 2006. The popularity of this paper exemplifies the growing interest in thematic analysis as a distinct method.

Qualitative research in criminology consists of research in the criminology field that employs qualitative methods. There are many applications of this research, and they can often intersect with quantitative research in criminology in order to create mixed method studies.

Social data science is an interdisciplinary field that addresses social science problems by applying or designing computational and digital methods. As the name implies, Social Data Science is located primarily within the social science, but it relies on technical advances in fields like data science, network science, and computer science. The data in Social Data Science is always about human beings and derives from social phenomena, and it could be structured data or unstructured data. The goal of Social Data Science is to yield new knowledge about social networks, human behavior, cultural ideas and political ideologies. A social data scientist combines cdomain knowledge and specialized theories from the social sciences with programming, statistical and other data analysis skills.

References

  1. 1 2 Lansford, Tom (2011). Kurian, George Thomas (ed.). The Encyclopedia of Political Science. Vol. 1–5. CQ Press. p. 1377. ISBN   978-1-933116-44-0.
  2. ↑ Gray, Paul S.; Williamson, John B.; Karp, David A.; Dalphin, John R. (2007-08-13). The Research Imagination: An Introduction to Qualitative and Quantitative Methods. Cambridge University Press. ISBN   978-1-139-46702-5.
  3. 1 2 3 4 King, Gary (1996-01-03). "On Political Methodology". ICPSR Data Holdings. Retrieved 2024-11-20.
  4. ↑ Taber, Charles S.; Timpone, Richard J. (1996-03-21). Computational Modeling. SAGE. ISBN   978-0-8039-7270-4.
  5. ↑ Nickerson, David W.; Rogers, Todd (2014). "Political Campaigns and Big Data". Journal of Economic Perspectives. 28 (2): 51–74. doi:10.1257/jep.28.2.51. ISSN   0895-3309.
  6. ↑ "How political campaigns use your data". Reuters. Retrieved 2024-11-20.
  7. 1 2 "How AI, TikTok, and Instagram Are Shaping the U.S. Election". Faculty of Arts and Sciences. 2024-11-03. Retrieved 2024-11-20.
  8. 1 2 3 4 Moses M., Laura; Box-Steffensmeier, Janet M. (Oct 23, 2023). "Oxford Handbook of Engaged Methodological Pluralism in Political Science". academic.oup.com. doi:10.1093/oxfordhb/9780192868282.013.49 . Retrieved 2024-11-20.
  9. ↑ Habehh, Hafsa; Gohel, Suril (2021-12-16). "Machine Learning in Healthcare". Current Genomics. 22 (4): 291–300. doi:10.2174/1389202922666210705124359. PMC   8822225 . PMID   35273459.
  10. ↑ "Students Are Using AI Already. Here's What They Think Adults Should Know | Harvard Graduate School of Education". www.gse.harvard.edu. 2024-09-10. Retrieved 2024-11-20.
  11. ↑ Savaget, Paulo; Chiarini, Tulio; Evans, Steve (November 5, 2018). "Science and Public Policy". academic.oup.com. Retrieved 2024-11-20.
  12. 1 2 "AI in Political Campaigns: How it's being used and the ethical considerations it raises | Media Relations | The George Washington University". Media Relations. Retrieved 2024-11-20.
  13. 1 2 Parsons, Lian (2020-10-26). "Ethical concerns mount as AI takes bigger decision-making role". Harvard Gazette. Retrieved 2024-11-20.
  14. ↑ Antje (2019-11-08). "10 Things to Know about How to Influence Policy with Research". The Commons. Retrieved 2024-11-20.
  15. ↑ Omari, Rose; Adams, Abdulai; Baah-Tuahene, Sylvia; Karbo, Ransford T.; Mensah, Cephas A.; Frempong, Godfred K.; Tetteh, Emmanuel K.; Quaison, Kwamena E. (2024-07-02). "Researchers' participation in the policy process: lessons from aflatoxin control in Ghana". Policy Design and Practice. 7 (3): 292–307. doi:10.1080/25741292.2024.2322760. ISSN   2574-1292.
  16. ↑ Parkhurst, Justin (2017). The Politics of Evidence: From evidence -based policy to the good governance of evidence. Taylor & Francis. ISBN   978-1-315-67500-8.


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