Abstract Details
Activity Number:
|
288
|
Type:
|
Contributed
|
Date/Time:
|
Tuesday, August 5, 2014 : 8:30 AM to 10:20 AM
|
Sponsor:
|
Survey Research Methods Section
|
Abstract #312271
|
View Presentation
|
Title:
|
Automated Survey Coding for German Occupations
|
Author(s):
|
Malte Schierholz*+
|
Companies:
|
|
Keywords:
|
coding ;
occupation ;
questionnaire design
|
Abstract:
|
Currently, most surveys ask for occupation with open-ended questions. The verbatim responses are coded afterwards into a classification with hundreds of categories and thousands of jobs, which is an error-prone, time-consuming and costly task. Our goal is to facilitate survey coding using machine learning methods. The idea is to use answers that were coded before to predict correct codes for new answers. Our method allows for further covariates in addition to the verbatim answer. We also account for the limited size of available training data. Performance is further improved when information from a dictionary is included. The proposed algorithms can be used for automated coding without human interaction but we expect it to be most helpful for computer-assisted coding.
|
Authors who are presenting talks have a * after their name.
Back to the full JSM 2014 program
|
2014 JSM Online Program Home
For information, contact jsm@amstat.org or phone (888) 231-3473.
If you have questions about the Professional Development program, please contact the Education Department.
The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.
Copyright © American Statistical Association.