Scaling Policy Preferences from Coded Political Texts

نویسندگان

  • Will Lowe
  • Kenneth Benoit
  • Slava Mikhaylov
  • Michael Laver
چکیده

Scholars wanting to estimate substantive quantities of interest, for example policy positions, from political texts typically apply a coding scheme to discrete text units such as words or sentences. Scales of policy positions, for example a left-right scale of economic policy, are typically built from the relative frequencies of text units coded into different categories. In this paper we reexamine the theoretical and linguistic basis for such scales, proposing a new alternative. This is based the logarithm of odds-ratios and is consistent with underlying political and linguistic mechanisms typically assumed to underlie text generation. We contrast this scale with previous approaches using coded text data from the Comparative Manifesto Project (CMP). We show that the logit scale we propose avoids widely acknowledged flaws in previous approaches. We validate the new scale using independent expert surveys of policy positions. Using existing CMP data, we show how to estimate more different policy dimensions, for more years, than has been possible before. We make this new dataset available, along with estimates of uncertainty for each measure. Finally, we draw some conclusions about the future design of coding schemes for political texts.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Scaling Policy Positions From Coded Units of Political Texts∗

Applying a coding scheme to discrete text units has long been the most common method for estimating substantive quantities of interest about the authors of these texts, whether for political, social, economic, or other substantive reasons. In political analysis, researchers typically build scales of policy positions from the relative frequencies of text units coded as left versus right policy c...

متن کامل

Tracking Amendments to Legislation and Other Political Texts with a Novel Minimum-Edit-Distance Algorithm: DocuToads

Political scientists often find themselves tracking amendments to political texts. As different actors weigh in, texts change as they are drafted and redrafted, reflecting political preferences and power. This study provides a novel solution to the problem of detecting amendments to political text based upon minimum edit distances. We demonstrate the usefulness of two language-insensitive, tran...

متن کامل

A Dynamic State-Space Model of Coded Political Texts

This article presents a new method of reconstructing actors’ political positions from coded political texts. It is based on a model that combines a dynamic perspective on actors’ political positions with a probabilistic account of how these positions are translated into emphases of policy topics in political texts. In the article it is shown how model parameters can be estimated based on a maxi...

متن کامل

Estimating Policy Positions from Political Texts

D eriving reliable and valid estimates of the policy positions of key actors is fundamental to the analysis of political competition. Various systematic methods have been used to do this, including surveys of voters, politicians, and political scientists, and the content analysis of policy documents. Each method has advantages and disadvantages but, for both theoretical and pragmatic reasons, p...

متن کامل

Estimating Uncertainty in Quantitative Text Analysis∗

Several methods have now become popular in political science for scaling latent traits— usually left-right policy positions—from political texts. Following a great deal of development, application, and replication, we now have a fairly good understanding of the estimates produced by scaling models such as “Wordscores”, “Wordfish”, and other variants (i.e. Monroe and Maeda’s two-dimensional esti...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2009