Online Sales Prediction: An Analysis With Dependency SCOR-Topic Sentiment Model
نویسندگان
چکیده
منابع مشابه
Dependency-based Topic-Oriented Sentiment Analysis in Microposts
In this paper, we present a method that exploits syntactic dependencies for topic-oriented sentiment analysis in microposts. The proposed solution is based on supervised text classification (decision trees in particular) and freely-available polarity lexicons in order to identify the relevant dependencies in each sentence by detecting the correct attachment points for the polarity words. Our ex...
متن کاملA Sentiment-aligned Topic Model for Product Aspect Rating Prediction
Aspect-based opinion mining has attracted lots of attention today. In this paper, we address the problem of product aspect rating prediction, where we would like to extract the product aspects, and predict aspect ratings simultaneously. Topic models have been widely adapted to jointly model aspects and sentiments, but existing models may not do the prediction task well due to their weakness in ...
متن کاملHidden Topic Sentiment Model
Various topic models have been developed for sentiment analysis tasks. But the simple topic-sentiment mixture assumption prohibits them from finding fine-grained dependency between topical aspects and sentiments. In this paper, we build a Hidden Topic Sentiment Model (HTSM) to explicitly capture topic coherence and sentiment consistency in an opinionated text document to accurately extract late...
متن کاملTopic Sentiment Change Analysis
Public opinions on a topic may change over time. Topic Sentiment change analysis is a new research problem consisting of two main components: (a) mining opinions on a certain topic, and (b) detect significant changes of sentiment of the opinions on the topic and identify possible reasons causing each such change. In this paper, we discuss topic sentiment change analysis using data on the Web. W...
متن کاملSentiment Topic Model with Decomposed Prior
This paper deals with the problem of jointly mining topics, sentiments, and the association between them from online reviews in an unsupervised way. Previous methods often treat a sentiment as a special topic and assume a word is generated from a flat mixture of topics, where the discriminative performance of sentiment analysis is not satisfied. A key reason is that providing rich priors on the...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Access
سال: 2019
ISSN: 2169-3536
DOI: 10.1109/access.2019.2919734