Limits of opinion-finding baseline systems
Generate an AI Snapshot to get a quick, structured summary of this paper.
A concise AI-generated summary of the paper will appear here once you click Generate AI Snapshot.
TL;DR
This work investigates how the underlying 'baseline' retrieval system performance affects the overall opinion-finding performance, and applies two effective opinion- finding techniques to all the baseline runs submitted to the TREC 2007 Blog track, and draws new insights and conclusions.
Abstract
In opinion-finding, the retrieval system is tasked with retrieving not just relevant documents, but which also express an opinion towards the query target entity. Most opinion-finding systems are based on a two-stage approach, where initially the system aims to retrieve relevant documents, which are then re-ranked according to the extent to which they are detected to be of an opinionated nature. In this work, we investigate how the underlying 'baseline' retrieval system performance affects the overall opinion-finding performance. We apply two effective opinion-finding techniques to all the baseline runs submitted to the TREC 2007 Blog track, and draw new insights and conclusions.