Exploiting Discourse Relations for Sentiment Analysis
نویسندگان
چکیده
The overall sentiment of a text is critically affected by its discourse structure. By splitting a text into text spans with different discourse relations, we automatically train the weights of different relations in accordance with their importance, and then make use of discourse structure knowledge to improve sentiment classification. In this paper, we utilize explicit connectives to predict discourse relations, and then propose several methods to incorporate discourse relation knowledge to the task of sentiment analysis. All our methods integrating discourse relations perform better than the baseline methods, validating the effectiveness of using discourse relations in Chinese sentiment analysis. We also automatically find out the most influential discourse relations and connectives in sentiment analysis. TITLE AND ABSTRACT IN CHINESE
منابع مشابه
A Bayesian Model for Joint Unsupervised Induction of Sentiment, Aspect and Discourse Representations
We propose a joint model for unsupervised induction of sentiment, aspect and discourse information and show that by incorporating a notion of latent discourse relations in the model, we improve the prediction accuracy for aspect and sentiment polarity on the sub-sentential level. We deviate from the traditional view of discourse, as we induce types of discourse relations and associated discours...
متن کاملCOMMIT at SemEval-2016 Task 5: Sentiment Analysis with Rhetorical Structure Theory
This paper reports our submission to the Aspect-Based Sentiment Analysis task of SemEval 2016. It covers the prediction of sentiment for a given set of aspects (e.g., subtask 1, slot 2) for the English language using discourse analysis. To that end, a discourse parser implementing the Rhetorical Structure Theory is employed and the resulting information is used to determine the context of each ...
متن کاملSentiment Analysis in Twitter with Lightweight Discourse Analysis
We propose a lightweight method for using discourse relations for polarity detection of tweets. This method is targeted towards the web-based applications that deal with noisy, unstructured text, like the tweets, and cannot afford to use heavy linguistic resources like parsing due to frequent failure of the parsers to handle noisy data. Most of the works in micro-blogs, like Twitter, use a bag-...
متن کاملUIR-PKU: Twitter-OpinMiner System for Sentiment Analysis in Twitter at SemEval 2015
Microblogs are considered as We-Media information with many real-time opinions. This paper presents a Twitter-OpinMiner system for Twitter sentiment analysis evaluation at SemEval 2015. Our approach stems from two different angles: topic detection for discovering the sentiment distribution on different topics and sentiment analysis based on a variety of features. Moreover, we also implemented i...
متن کاملA Preliminary Investigation into Sentiment Analysis of Informal Political Discourse
With the rise of weblogs and the increasing tendency of online publications to turn to message-board style reader feedback venues, informal political discourse is becoming an important feature of the intellectual landscape of the Internet, creating a challenging and worthwhile area for experimentation in techniques for sentiment analysis. We describe preliminary statistical tests on a new datas...
متن کامل