Quantitative Text Analysis (TCD 2018)

Overview Objectives Detailed Course Schedule Week 1: Introduction and issues in quantitative text analysis Week 2: Quantitative methods for comparing texts Week 3: Automated dictionary-based approaches Week 4: Machine learning and scaling for texts Week 5: Scaling models Final Assignment References When and where: 16 February, 23 February, 9 March, 16 March, 23 March 2018; Arts Building 3020.

Quantitative Text Analysis (TCD 2016)

Meeting times 5 February, 12 February, 11 March, 18 March. Course Handout Short Outline The course surveys methods for systematically extracting quantitative information from political text for social scientific purposes, starting with classical content analysis and dictionary-based methods, to classification methods, and state-of-the-art scaling methods and topic models for estimating quantities from text using statistical techniques.

Data Mining and Statistical Learning

2015, Trinity College, Dublin, Department of Political Science Instructor: Prof Kenneth Benoit, LSE Details: Class meets MONDAYS in Feb-March from 14:00 – 16:30, with one exception on Day 2 (see below)

The Quantitative Analysis of Textual Data (NYU Fall 2014)

Sponsored by: NYU Department of Politics 2014 pdf version of Course handout Instructor: Prof Kenneth Benoit, LSE Details: Class meets TUESDAYS 10:00 – 11:50 in Room 217 Note: As the class proceeds, I will add resources (slides, R code, text datasets, problem sets) to each session below.

How to batch convert pdf files to text

Frequently I am asked: I have a bunch of pdf files, how can I convert them to plain text so that analyze them using quantitative techniques? Here is my recommendation.

Quantitative Text Analysis 2E, Essex 2014

Quantitative Text Analysis 2E Essex Summer School 2014 Course handout Instructor: Prof Kenneth Benoit, LSE TA: Dr. Paul Nulty, LSE Day 1: Quantitative text analysis overview and fundamentals slides demonstration .

Quantitative Text Analysis (TCD)

Short Outline The course surveys methods for systematically extracting quantitative information from text for social scientific purposes, starting with classical content analysis and dictionary-based methods, to classification methods, and state-of-the-art scaling methods and topic models for estimating quantities from text using statistical techniques.

MY560: Supervised Methods for Classifying and Scaling Texts

Here are the slides and files from my “Introduction to Supervised Methods for Classifying and Scaling Texts” workshop in our MY560 series from May 28, 2013. Slides here Lab Exercise here Files for lab exercise: Movie Reviews and the amicus briefs

ME104 Linear Regression Analysis, 2012

ME104 Linear Regression Analysis Professor Kenneth Benoit London School of Economics and Political Science Course Handout as pdf Objectives and Learning Outcomes This course focuses on building a greater understanding, theoretical underpinning, and tools for applying the linear regression model and its generalizations.

Computer-Assisted Text Analysis (Essex Summer School)

This concerns the short course I am teaching at the Essex Summer School in Social Science Data Analysis, University of Essex, from 11-22 July 2011. Course handout (syllabus) Day 1: Introduction to Computer-Assisted TextAnalysis

EUI Multi-Level Models Course

An Introduction to Multi-Level Models (Using Stata) European University Institute, May 23–27, 2011 Professor Kenneth Benoit Methodology Institute, London School of Economics Course handout here. Readings are available from Mark Franklin’s Dropbox account for this course.

CEU Computerized Text Course Announcements

This post concerns the short course I am teaching at Central European University, Budapest from 14-21 April 2011. Stay tuned to this post for future announcements. The course handout (syllabus) is available here.

Principles of Comparative Research Week 7 Outline Guidelines

On Friday, November 12 your five-page (maximum) outline of your research proposal is due. In brief: This is designed to be a shorter version of your final assignment research proposal, providing a more summary version of the project will propose in fuller form at the end of the term.

So you want to get a PhD in Political Science ...

This is painfully funny… if completely, ahem, unfounded.

New MSc in International Politics

New MSc in International Politics from the Department of Political Science, Trinity College Dublin This new M.Sc. in International Politics offers graduate students a combination of rigorous training in the study of international politics with a comprehensive empirical approach to understanding many prominent problems in contemporary world politics, especially topics where domestic and international politics cannot be understood in isolation from each other.

PhD Scholarships in Political Science at Trinity College Dublin

Fully-funded studentships are available for study in the PhD programme in Political Science at Trinity College Dublin, paying tuition plus a stipend of up to €15,000 per year. Application for this financial support is automatically considered as part of the normal admissions process.

Data Analysts Captivated by R's Power

Here’s a recent article published in the New York Times about R, the freely available statistical package: “Data Analysts Captivated by R’s Power” By ASHLEE VANCE Published: January 7, 2009

Social scientists use real data

Here’s a good one from for all you PhD students:

Spring 2009 course information now posted

I have now added the detailed course outlines to my web page for the courses I am teaching in Spring 2009. These are: Introduction to Quantitative Research Methods (MSc) Quantitative Methods II (PhD) 

MSc Modules on Electoral, Party Systems

As promised I have now posted the presentations from the weeks in Government Institutions. These are in pdf format so should be readable by everyone. Note that you must be on the local TCD network (or using the VPN or proxy server) to access these files.

Course-related discussions

This will be a place for posting announcements (and comments) related to courses I teach.