Lexicon based Sentiment Analysis for Twitter
نویسندگان
چکیده
منابع مشابه
Sentiment Analysis on Twitter through Topic-Based Lexicon Expansion
Supervised learning approaches are domain-dependent and it is costly to obtain labeled training data from different domains. Lexiconbased approaches enjoy stable performance across domains, but often cannot capture domain-dependent features. It is also hard for lexiconbased classifiers to identify the polarities of abbreviations and misspellings, which are common in short informal social text b...
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Lexicon-Based approaches to Sentiment Analysis (SA) differ from the more common machine-learning based approaches in that the former rely solely on previously generated lexical resources that store polarity information for lexical items, which are then identified in the texts, assigned a polarity tag, and finally weighed, to come up with an overall score for the text. Such SA systems have been ...
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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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ژورنال
عنوان ژورنال: International Journal for Research in Applied Science and Engineering Technology
سال: 2020
ISSN: 2321-9653
DOI: 10.22214/ijraset.2020.6281