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A Fuzzy Approach to Sentiment Analysis at the Sentence Level
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Best Practices of Convolutional Neural Networks for Question Classification
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Hesitant Fuzzy Linguistic Preference Utility Set and Its Application in Selection of Fire Rescue Plans
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An interaction consensus in group decision making under distributed trust information
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Successes and challenges in developing a hybrid approach to sentiment analysis
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Abstract:
The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link. ; This article covers some success and learning experiences attained during the developing of a hybrid approach to Sentiment Analysis (SA) based on a Sentiment Lexicon, Semantic Rules, Negation Handling, Ambiguity Management and Linguistic Variables. The proposed hybrid method is presented and applied to two selected datasets: Movie Review and Sentiment Twitter datasets. The achieved results are compared against those obtained when Nai ve Bayes (NB) and Maximum Entropy (ME) supervised machine learning classification methods are used for the same datasets. The proposed hybrid system attained higher accuracy and precision scores than NB and ME, which shows its superiority when applied to the SA problem at the sentence level. Finally, an alternative strategy to calculating the orientation polarity and polarity intensity in one step instead of the two steps method used in the hybrid approach is explored. The analysis of the yielded mixed results achieved with this alternative approach shows its potential as an aid in the computation of semantic orientations and produced some lessons learnt in developing a more effective mechanism to calculating the orientation polarity and polarity intensity.
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Keyword:
Computational linguistic; Computing with Sentiments; Fuzzy sets; Natural language processing; Sentiment Analysis; Sentiment rules; SentiWordNet; Uninorms
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URL: https://doi.org/10.1007/s10489-017-0966-4 http://hdl.handle.net/2086/14154
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A minimum adjustment cost feedback mechanism based consensus model for group decision making under social network with distributed linguistic trust
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A consensus approach to the sentiment analysis problem driven by support-based IOWA majority
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Successes and challenges in developing a hybrid approach to sentiment analysis
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A Consensus Approach to the Sentiment Analysis Problem Driven by Support-Based IOWA Majority
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A Hybrid Approach to Sentiment Analysis with Benchmarking Results
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14 |
A Hybrid Approach to the Sentiment Analysis Problem at the Sentence Level
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