Latent aspect rating analysis on review text data
University of Illinois Urbana-Champaign
Abstract
In this paper, we define and study a new opinionated text data analysis problem called Latent Aspect Rating Analysis (LARA), which aims at analyzing opinions expressed about an entity in an online review at the level of topical aspects to discover each individual reviewer's latent opinion on each aspect as well as the relative emphasis on different aspects when forming the overall judgment of the entity. We propose a novel probabilistic rating regression model to solve this new text mining problem in a general way. Empirical experiments on a hotel review data set show that the proposed latent rating regression model can effectively solve the problem of LARA, and that the detailed analysis of opinions at the…
Citation impact
- FWCI
- 35.91
- Percentile
- 100%
- References
- 30
Authors
3Topics & keywords
- Automatic summarization
- Computer science
- Ranking (information retrieval)
- Set (abstract data type)
- Information retrieval
- Latent variable
- Probabilistic logic
- Sentiment analysis