TY - JOUR
T1 - Analyzing product comparisons on discussion boards
AU - Feldman, Ronen
AU - Fresko, Moshe
AU - Goldenberg, Jacob
AU - Netzer, Oded
AU - Ungar, Lyle
N1 - Publisher Copyright:
© Springer-Verlag Berlin Heidelberg 2014.
PY - 2014
Y1 - 2014
N2 - Product discussion boards are a rich source of information about consumer sentiment about products, which is being increasingly exploited. Most sentiment analysis has looked at single products in isolation, but users often compare different products, stating which they like better and why. We present a set of techniques for analyzing how consumers view product markets. Specifically, we extracted relative sentiment analysis and comparisons between products, to understand what attributes users compare products on, and which products they prefer on each dimension. We illustrate these methods in an extended case study analyzing the sedan car markets.
AB - Product discussion boards are a rich source of information about consumer sentiment about products, which is being increasingly exploited. Most sentiment analysis has looked at single products in isolation, but users often compare different products, stating which they like better and why. We present a set of techniques for analyzing how consumers view product markets. Specifically, we extracted relative sentiment analysis and comparisons between products, to understand what attributes users compare products on, and which products they prefer on each dimension. We illustrate these methods in an extended case study analyzing the sedan car markets.
KW - Information extraction
KW - Sentiment analysis
KW - Text mining
UR - http://www.scopus.com/inward/record.url?scp=84916213911&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-45321-2_18
DO - 10.1007/978-3-642-45321-2_18
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AN - SCOPUS:84916213911
SN - 0302-9743
VL - 8001
SP - 399
EP - 408
JO - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
JF - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ER -