Sentiment Analysis with Automatically Constructed Lexicon and Three-Way Decision
نویسندگان
چکیده
An unsupervised sentiment analysis method is presented to classify user comments on laptops into positive ones and negative ones. The method automatically extracts informative features in testing dataset and labels the sentiment polarity of each feature to make a domainspecific lexicon. The classification accuracy of this lexicon will be compared to that with an existing general sentiment lexicon. Besides, the concept of three-way decision will be applied in the classifier as well, which combines lexicon-based methods and supervised learning methods together. Results indicate that the overall performance can reach considerable improvements with three-way decision.
منابع مشابه
On the Automatic Learning of Sentiment Lexicons
This paper describes a simple and principled approach to automatically construct sentiment lexicons using distant supervision. We induce the sentiment association scores for the lexicon items from a model trained on a weakly supervised corpora. Our empirical findings show that features extracted from such a machine-learned lexicon outperform models using manual or other automatically constructe...
متن کاملA Supervised Method for Constructing Sentiment Lexicon in Persian Language
Due to the increasing growth of digital content on the internet and social media, sentiment analysis problem is one of the emerging fields. This problem deals with information extraction and knowledge discovery from textual data using natural language processing has attracted the attention of many researchers. Construction of sentiment lexicon as a valuable language resource is a one of the imp...
متن کاملDifferential Influence of Blogs Across Different Stages of Decision Making: The Case of Venture Capitalists
In this work, we followed the sentiment analysis literature, and used supervised learning methods, which take manually classified data (corpus) as input and automatically extract features (combination of words and parts of speech of words) for sentiment analysis (Dave et al. 2003; Ghose and Ipeirotis 2011; Pang et al. 2002; Shanahan et al. 2006). These supervised methods do not rely on manually...
متن کاملیک چارچوب نیمهنظارتی مبتنی بر لغتنامه وفقی خودساخت جهت تحلیل نظرات فارسی
With the appearance of Web 2.0 and 3.0, users’ contribution to WWW has created a huge amount of valuable expressed opinions. Considering the difficulty or impossibility of manually analyzing such big data, sentiment analysis, as a branch of natural language processing, has been highly considered. Despite the other (popular) languages, a limited number of research studies have been conducted in ...
متن کاملIncorporating Lexicon Knowledge into SVM Learning to Improve Sentiment Classification
Two typical approaches to sentiment analysis are lexicon look up and machine learning. Even though recent studies have shown that machine learning approaches in general outperform the lexicon look up approaches, completely ignoring the knowledge encoded in sentiment lexicons may not be optimal. We present an alternative method that incorporates sentiment lexicons as prior knowledge with machine...
متن کامل