DocumentCode
2227761
Title
Learning to perform moderation in online forums
Author
Arnt, Andrew ; Zilberstein, Shlomo
Author_Institution
Dept. of Comput. Sci., Massachusetts Univ., Amherst, MA, USA
fYear
2003
fDate
13-17 Oct. 2003
Firstpage
637
Lastpage
641
Abstract
Online discussion forums are a valuable resource for people looking to find information, discuss ideas, and get advice on the Internet. Unfortunately, many forums have too much activity and information available, resulting in information overload. Moderation systems are implemented in some forums as a way to handle this problem, but due to sparsity issues, they are often not sufficient. We describe a novel method for learning from past moderations to develop a classifier that can perform automated moderation and thus address the sparsity problem. Additionally, we discuss the possibility of training a moderating classifier on a moderated forum and then applying it to an otherwise unmoderated forum.
Keywords
Internet; classification; information filters; information retrieval; learning (artificial intelligence); Internet; information overload; machine learning; moderated forum; moderating classifier; moderation systems; online discussion forums; sparsity issues; unmoderated forum; Accuracy; Aggregates; Collaboration; Computer science; Discussion forums; Filtering algorithms; Filters; Humans; Recommender systems; Search engines;
fLanguage
English
Publisher
ieee
Conference_Titel
Web Intelligence, 2003. WI 2003. Proceedings. IEEE/WIC International Conference on
Print_ISBN
0-7695-1932-6
Type
conf
DOI
10.1109/WI.2003.1241285
Filename
1241285
Link To Document