[PDF] Top 20 Effective Use of Linguistic Features for Sentiment Analysis of Korean
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Effective Use of Linguistic Features for Sentiment Analysis of Korean
... The stative noun 흥분 hungpwun ‘excitement’ in example (7) has the base positive value +1 and the value for the word is strengthened to +2 by the effect of the intensifier adverb 저리 celi ‘like that’. Up to this point, the ... See full document
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Sentiment classification on customer feedback data: noisy data, large feature vectors, and the role of linguistic analysis
... of features, and both training and classification for linear SVMs are fast with optimized learning ...we use John Platt’s Sequential Minimal Optimization (SMO) tool (Platt ... See full document
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Generalized Sentiment Bearing Expression Features for Sentiment Analysis
... extract sentiment-bearing expression features derived from dependency ...directly use dependency relations generated by a parser, we propose a set of heuristic rules to detect both explicit and ... See full document
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INTELLIGENT SELF TUNING PID CONTROLLER USING HYBRID IMPROVED PARTICLE SWARM OPTIMIZATION FOR ULTRASONIC MOTOR
... aspect-dependent sentiment lexicons from online customer ...dependent sentiment lexicon refers to aspect- specific opinion words with aspect-aware sentiment polarities regarding specific ... See full document
12
Leveraging Cognitive Features for Sentiment Analysis
... cognitive features de- rived from readers’ eye movement ...significantly effective for text with complex constructs, leading to an improvement of ...gaze-based features and (b) multi-view ... See full document
11
Influence Of Syntactic, Semantic And Stylistic Features For Sentiment Identification Of Messages Using Svm Classifier
... quite effective in dealing with text data analysis ...the sentiment of ...syntactic features used in sentiment analysis [14]. In sentiment analysis, word N-grams ... See full document
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KOSAC: A Full-Fledged Korean Sentiment Analysis Corpus
... This paper aims to introduce the Korean Sentiment Analysis Corpus named KOSAC. KOSAC is a corpus consisting of 332 news articles taken from the Sejong Syntactic Parsed Corpus. These sentences have ... See full document
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Cross-Linguistic Sentiment Analysis: From English to Spanish
... we use the 400 text Epinions corpus (50 texts in each of eight different product types), the other 1,900 texts in the Polarity Dataset (Movie), and a 2,400 text corpus of camera, printer, and stroller reviews ... See full document
5
Gulf Arabic Linguistic Resource Building for Sentiment Analysis
... using sentiment lexicon designed for Modern Standard Arabic (MSA) to classify sentiments in Gulf ...Arabic sentiment lexicon ...and use orthographic features, namely spellings, emoticons, ... See full document
6
Sentiment Analysis of Tunisian Dialects: Linguistic Ressources and Experiments
... The sentiment clas- sifier is built by extracting discriminative fea- tures from annotated data and applying a Machine learning algorithm such as Support Vector Ma- chines (SVM), Na¨ıve Bayes (NB) and Logistic re- ... See full document
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Automatic Identification of Suicide Notes from Linguistic and Sentiment Features
... Psychological studies have shown that our state of mind can manifest itself in the linguistic features we use to communi- cate. Recent statistics in suicide preven- tion show that young people are ... See full document
6
Combining Social Cognitive Theories with Linguistic Features for Multi-genre Sentiment Analysis
... simpler linguistic structures to those posts with more complicated ...the sentiment on the tar- get “Mitt Romney” from the following post: “Paul is the complete opposite of ...“positive” sentiment ... See full document
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Effective Use of Linguistic and Contextual Information for Statistical Machine Translation
... to use a stochastic gradient descent (SGD) or Perceptron like online learning algo- rithm to optimize the weights of these features directly for MT (Shen et ...to use a substan- tially large ... See full document
9
Linguistic correlates of style: authorship classification with deep linguistic analysis features
... all features, including length features, consistently outperforms all other ...stricting features to those that only utilize shallow linguistic analysis, such as the POS trigram fea- ... See full document
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<p>Bibliometric Analysis of Research Assessing the Use of Acupuncture for Pain Treatment Over the Past 20 Years</p>
... quantitative analysis method that uses mathematical and statistical tools to measure the inter- relationships and impacts of publications within a given area of ... See full document
10
Exploring the Use of Linguistic Features in Domain and Genre Classification
... Karlgren and Cutting, 1994 reports good results in a genre clas- sification task based on a subset of these features, while Kessler et al., 1997 show t h a t a prudent selection of cues [r] ... See full document
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Towards the Extraction of Customer to Customer Suggestions from Reviews
... tion of suggestion easily distinguishes sugges- tions from other kind of text. However, when suggestions are required to be identified in the space of customer reviews, there seems to be a tendency to consider most of ... See full document
9
Violence Rating Prediction from Movie Scripts
... to linguistic features, works have explored the use of social network meta-data (Pavlopou- los, Malakasiotis, and Androutsopoulos 2017) with the ef- fectiveness of this approach still up for debate ... See full document
8
Use of Deep Linguistic Features for the Recognition and Labeling of Semantic Arguments
... the features that accom- pany this structure, form a better basis for determin- ing semantic role ...across linguistic frameworks, unlike the very partic- ular surface-syntactic choices made by the ... See full document
8
A Multi sentiment resource Enhanced Attention Network for Sentiment Classification
... the sentiment polarity of a given text as positive, negative, or more fine-grained ...up sentiment classifiers using supervised machine learning approaches, such as support vector machine (SVM) (Pang et ... See full document
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