Content Analysis Through the Machine Learning Mill

We present an analysis of partial automation of content analysis using machine learning methods. We use a decision-tree induction system to learn from manually categorized negotiation transcripts of electronic buyer-seller negotiations. The data we use were gathered using the Web-based negotiation s...

Full description

Saved in:
Bibliographic Details
Published in:Group decision and negotiation 2007-07, Vol.16 (4), p.335-346
Main Authors: Nastase, Vivi, Koeszegi, Sabine, Szpakowicz, Stan
Format: Article
Language:English
Subjects:
Automatic text analysis
Automation
Bargaining
Communication
Computer mediated communication
Content analysis
Datasets
Decision making
Decision trees
Groups
Induction
Information technology
Internet
Learning
Linguistics
Machine learning
Negotiation
Negotiations
Qualitative research
Research methodology
Social psychology
Studies
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:We present an analysis of partial automation of content analysis using machine learning methods. We use a decision-tree induction system to learn from manually categorized negotiation transcripts of electronic buyer-seller negotiations. The data we use were gathered using the Web-based negotiation support systems Inspire and SimpleNS. We experiment with various ways of representing the data to find the solution that gives the best results. The experiments show that we can identify, in relatively small data sets, linguistic features of interest for the detection of negotiation behaviour and negotiation-specific topics. [PUBLICATION ABSTRACT]
ISSN:0926-2644
1572-9907
DOI:10.1007/s10726-006-9053-7