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開講年度 2016年度 開講箇所 大学院政治学研究科
Polimetrics(Advanced Scaling Techniques in Political Science)(GPE・Curini)

担当教員 クリーニ ルイージ
学期曜日時限 秋クォーター  水2-3
科目区分 国際政経・コア科目 配当年次 1年以上 単位数 2
使用教室 3-902(学部PCルーム) キャンパス 早稲田
科目キー 3101012F46 科目クラスコード 01
授業で使用する言語 英語
  コース・コード POLX613L
大分野名称 政治学
中分野名称 政治学
小分野名称 現代政治/政治過程
レベル 修士レベル 授業形態 講義


最終更新日時:2016/04/27 10:57:01

副題 Applied Polimetrics in Political Science: from preferences to spatial strategies
授業概要 This course is aimed to teach students the main theories and the connected methods available in the literature to estimate the policy space within which the political competition occurs as well as to measure the positions of political actors interacting in such space. A special attention will be also devoted to the analysis of information coming from social media. Moreover, students will learn to apply the spatial theory of voting in different settings to better understand the entire political cycle: from electoral competition to government formation. To this aim, beyond Stata or R, different open-source software will be employed during the classes. Lab sessions are offered for ‘hands-on’ experiences to learn the techniques.
授業の到達目標 Students will learn how to measure the positions of political actors through different methods. By learning how to apply the polimetric technique, students are able to test various theories in political science ranging from party competition to government formation.


Morning (topic)


(software & topic)



What we mean by spatial preferences of political actors and how to measure them: an introduction



CyberSenate software: an introduction

Benoit, K. and Laver, M. (2006). Party policy in modern democracies. London: Routledge, chapters 1-4

Laver M. and Hunt, W. (1990). Policy and Party Competition, Routledge, Introduction and Chapter 1

Laver M. (2001). Estimating the Policy Positions of Political Actor, Routledge, Chapter 1


Coalition Spatial Theory

(part I)

CyberSenate software: an application

Schofield, N. (1993). Political Competition and Multiparty Coalition Governments. European Journal of Political Research 23: 1-33.

Schofield N. (1995). Coalition Politics. A formal model and empirical analysis, Journal of Theoretical Political 7(3): 245-281


Coalition Spatial Theory

(part II)

CyberSenate software: an application

Tsebelis, G. (2002). Veto Players. How Institutions Work. Princeton, NJ: Princeton University Press, Chapter 1


Mass surveys, expert surveys and the problem of voter projection


Stata: an application to the Japanese case

Benoit, K. and Laver, M. (2006). Party policy in modern democracies. London: Routledge, chapter 5


Curini, Luigi (2010). Experts' Political Preferences and Their Impact on Ideological Bias, Party Politics, 16(3), 299-321


The Comparative Manifesto Project: from manifestoes to positions








Stata: an application to comparative data









Budge, I., and Laver, M. (1992). Coalition theory, government policy and party policy. In M. Laver and I. Budge (Eds.), Party policy and government coalitions (pp. 1-64). New York, NY: St. Martin’s.


Laver, Michael, and John Garry (2000). Estimating policy positions from political texts. American Journal of Political Science 44(3):619–34.


Lowe William, Kenneth Benoit, Slava Mikhaylov, and Michael Laver (2011). Scaling Policy Preferences From Coded Political Texts. Legislative Studies Quarterly 26(1): 123-155


Gabel, Matthew, and John Huber (2000). Putting Parties in Their Place, American Journal of Political Sciences, 44, 94-103.


From words to positions (part 1)








Stata + R: an application to comparative data








Laver, Michael, Kenneth Benoit, and John Garry (2003). Extracting policy positions from political texts using words as data. American Political Science Review 97(02): 311–31.


Lowe, Will (2008). Understanding wordscores. Political Analysis 16(4): 356–71


From words to positions (part 2)











R: an application to the Japanese (and Italian) case











Slapin, Jonathan B. and Sven-Oliver Proksch (2008). A Scaling Model for Estimating Time-Series Party Positions from Texts, American Journal of Political Science 52(3): 705-722.


Proksch, Sven-Oliber, and Slapin, Jonathan B. (2009) How to Avoid Pitfalls in Statistical Analysis of Political Texts: The Case of Germany. German Politics, 18(3): 323-344


Analyzing social media










VOICES from the Blogs platform: an application to a selected case








Hopkins, D. and G. King( 2010). A Method of Automated Nonparametric Content Analysis for Social Science. American Journal of Political Science 54(1): 229-247.


Ceron Andrea, Curini Luigi, and Stefano M. Iacus iSA: a fast, scalable and accurate algorithm for sentiment analysis of social media content, Information Sciences, forthcoming

教科書 Please see the weekly references above.
参考文献 Please see the weekly references above.
割合 評価基準
試験: 70% Students are expected to write a term paper at the end of the quarter by applying the polymetric technique learned in the course.
平常点評価: 30% Students are expected to attend the class and follow the content taught each week.
備考・関連URL Most of the dataset and scripts used during classes will be made available here:


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