Lexicon-enhanced sentiment analysis framework using rule-based classification scheme
نویسندگان
چکیده
منابع مشابه
Lexicon-enhanced sentiment analysis framework using rule-based classification scheme
With the rapid increase in social networks and blogs, the social media services are increasingly being used by online communities to share their views and experiences about a particular product, policy and event. Due to economic importance of these reviews, there is growing trend of writing user reviews to promote a product. Nowadays, users prefer online blogs and review sites to purchase produ...
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We propose a novel method for counting sentiment orientation that outperforms supervised learning approaches in time and memory complexity and is not statistically significantly different from them in accuracy. Our method consists of a novel approach to generating unigram, bigram and trigram lexicons. The proposed method, called frequentiment, is based on calculating the frequency of features (...
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General knowledge sentiment lexicons have the advantage of wider term coverage. However, such lexicons typically have inferior performance for sentiment classification compared to using domain focused lexicons or machine learning classifiers. Such poor performance can be attributed to the fact that some domain-specific sentiment-bearing terms may not be available from a general knowledge lexico...
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One of the widely used approaches to Sentiment Analysis (SA) is lexicon-based approach that depends on sentiment-annotated lexical resources (such as SentiWordNet (SWN)). A broad variety of such resources are Synsetbased Lexical Databases (SLDs) (e.g. SWN is based on WordNet (WN)) and represent sentiment degrees of synonym groups of LDs, called “synsets.” However, synsets themselves were open t...
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The vast information related to products and services available online, of both objective and subjective nature, can be used to provide contextualized suggestions and guidance to possible new customers. User feedback and comments left on different shopping websites, portals and social media have become a valuable resource, and text analysis methods have become an invaluable tool to process this...
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ژورنال
عنوان ژورنال: PLOS ONE
سال: 2017
ISSN: 1932-6203
DOI: 10.1371/journal.pone.0171649