IOA: Improving SVM Based Sentiment Classification Through Post Processing
نویسندگان
چکیده
This paper describes our systems for expression-level and message-level sentiment analysis – two subtasks of SemEval-2015 Task 10 on sentiment analysis in Twitter. First we built two baseline systems for the two subtasks using SVM with a variety of features. Then we improved the systems through model iteration and probability-output weighting respectively. Our submissions are ranked the 3rd and 2nd among eleven teams on the 2015 test set and progress test set in subtask A and the 7th and 4th among 40 teams on the two test sets respectively in subtask B.
منابع مشابه
Sentiment Classification of Movie Reviews Using Hybrid Method
the area of sentiment mining (also called sentiment extraction, opinion mining, opinion extraction, sentiment analysis, etc.) has seen a large increase in academic interest in the last few years. Researchers in the areas of natural language processing, data mining, machine learning, and others have tested a variety of methods of automating the sentiment analysis process. In this research work, ...
متن کاملImproved Optimized Sentiment Classification On Dynamic Tweets
Real time Sentiment analysis is a subfield of Natural Language Processing concerned with the determination of opinion and subjectivity in a text, which has many applications. In this paper, classifiers for sentiment analysis of user opinion towards through comments and tweets sing Support Vector Machine (SVM) is described. The goal is to develop a classifier that performs sentiment analysis, by...
متن کاملSentiment Analysis of Restaurant Reviews Using Hybrid Classification Method
The area of sentiment mining (also called sentiment extraction, opinion mining, opinion extraction, sentiment analysis, etc.) has seen a large increase in academic interest in the last few years. Researchers in the areas of natural language processing, data mining, machine learning, and others have tested a variety of methods of automating the sentiment analysis process. In this research work, ...
متن کاملUse of negation phrases in automatic sentiment classification of product reviews
This paper reports a study in automatic sentiment classification, i.e., automatically classifying documents as expressing positive or negative sentiments. The study investigates the effectiveness of using a machine-learning algorithm, support vector machine (SVM), on various text features to classify on-line product reviews into recommended (positive sentiment) and not recommended (negative sen...
متن کاملAspect Level Sentiment Classification with Deep Memory Network
We introduce a deep memory network for aspect level sentiment classification. Unlike feature-based SVM and sequential neural models such as LSTM, this approach explicitly captures the importance of each context word when inferring the sentiment polarity of an aspect. Such importance degree and text representation are calculated with multiple computational layers, each of which is a neural atten...
متن کامل