Difference between revisions of "Topic Model Approach to Authority Identification"
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== Dataset Description == | == Dataset Description == | ||
| + | The authors have reported results on two datasets. | ||
| + | * [[UsesDataset::GoodReads Data ]] | ||
== Motivation == | == Motivation == | ||
Revision as of 19:19, 1 October 2012
This a Paper reviewed for Social Media Analysis 10-802 in Fall 2012.
Contents
Citation
author = {Alexandre Passos and
Jacques Wainer and
Aria Haghighi},
title = {What do you know? A topic-model approach to authority identification},
journal = {NIPS 2010 Workshop on Computational Social Science and the Wisdom of the Crowds},
year = {2010}
Online version
What do you know? A topic-model approach to authority identification
Summary
In this paper the authors present a preliminary study of basic approaches to the problem of identifying authoritative documents in a given domain using textual content and report their best performing approach using Hierarchical Topic Models [Blei et al, 2004]. Authoritative documents are ones which exhibit novel and relevant information relative to a document collection while demonstrating domain knowledge. Authors define authoritativeness identification task as a ranking problem and focus on product (book and restaurant) reviews utilizing user votes as proxy for helpfulness and authoritativeness.
Dataset Description
The authors have reported results on two datasets.
