[PDF] Top 20 Linguistic Linked Data for Sentiment Analysis
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Linguistic Linked Data for Sentiment Analysis
... An interesting aspect of lemon-based ontology lexicalisation is the use of URIs for uniquely iden- tifying all objects defined by the lemon model (lex- icons, lexical entries, words, phrases, forms, vari- ants, senses, ... See full document
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Sentiment Analysis of Tunisian Dialects: Linguistic Ressources and Experiments
... In this paper, we present an application of sentiment analysis to the Tunisian dialect. One of the primary problems is the lack of annotated data. To overcome this problem, we start by using and ... See full document
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Transforming the Data Transcription and Analysis Tool Metadata and Labels into a Linguistic Linked Open Data Cloud Resource
... the Data Transcription and Analysis Tool ...and data primarily for the study of language acquisition, either monolingual or ...language data management and ...naturalistic data, it also ... See full document
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Gulf Arabic Linguistic Resource Building for Sentiment Analysis
... Arabic sentiment analysis is an active area where many works have been done recently for various ...of linguistic resources for Gulf Arabic, namely lexicons for sense disambiguation, sentiment ... See full document
6
Cross-Linguistic Sentiment Analysis: From English to Spanish
... Support Vector Machine (SVM) classifiers, built with the sequential minimal optimization algorithm included in the WEKA software suite [20], with a linear kernel and testing done with 10-fold cross-validation. We trained ... See full document
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INTELLIGENT SELF TUNING PID CONTROLLER USING HYBRID IMPROVED PARTICLE SWARM OPTIMIZATION FOR ULTRASONIC MOTOR
... of sentiment analysis methods to classify web for opinions in multiple languages was proposed by Abbasi et al ...for sentiment classification of English and Arabic ...review data set and ... See full document
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Towards the Representation of Hashtags in Linguistic Linked Open Data Format
... basic Linguistic Linked Open Data (LLOD) infrastructure for hashtags from social media ...of data-driven decomposition of multi-element hashtags, the linking of spelling variants, and ... See full document
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Sentiment Analysis Of Twitter Data
... Sentiment analysis involves several research fields: - natural language processing, computational linguistics and text ...raw data, often in text ...subjective data, like images, sounds and ... See full document
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Big Data: Deep Learning for financial sentiment analysis
... Big Data has been in use since the ...Big Data and defines it as follows: “Big Data is high-volume, high-velocity and/or high-variety information assets that demand cost-effective, innova- tive forms ... See full document
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Feature and Sentiment based Linked Instance RDF Data towards Ontology based Review Categorization
... the analysis in opinion ...the sentiment of the ...context data also supports for future ontology based analysis taking support of Wordnet lexical database for word sense disambiguation and ... See full document
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Identifying the sentiment styles of YouTube’s vloggers
... audio data, videos in which the vlogger is “talking more, faster, and using few pauses” receive more views on average (Biel and Gatica-Perez, ...the linguistic content of YouTube ...the linguistic ... See full document
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Effective Use of Linguistic Features for Sentiment Analysis of Korean
... proposed linguistic methods obtain higher results than TFIDF, except in the cases of F-measure score of the subtopic news article corpus which do not use a chunking ...Korean linguistic characteristics ... See full document
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Sentiment classification on customer feedback data: noisy data, large feature vectors, and the role of linguistic analysis
... the sentiment classification task by using features based on deep linguistic analysis or whether surface-based features would ...that linguistic features contribute to the overall accuracy of ... See full document
7
A Linked Data Model for Multimodal Sentiment and Emotion Analysis
... textual sentiment analysis, as NIF focuses on annotation of ...Big Linked Data Platform for multimedia and multilingual sentiment and emotion ... See full document
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Twitter Sentiment Analysis
... above sentiment analysis could be used for politics ...textual analysis as a base to derive ...this analysis were very much similar to the actual results of the ...of sentiment ... See full document
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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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Sentiment Analysis of Twitter Data
... Another significant effort for sentiment classifica- tion on Twitter data is by Barbosa and Feng (2010). They use polarity predictions from three websites as noisy labels to train a model and use 1000 ... See full document
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Review on ‘Big Data Sentiment Analysis’
... Opinions matter a lot in order to take any decision for the sake of any organisation or somewhere else. Before taking any crucial decision, taking opinions is must but analysing the result is also of the same importance. ... See full document
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Sentiment Analysis on Twitter Data
... topic-based sentiment analysis that extracts, maps, and measures customer opinions; (2) stream analysis identifying interesting tweets depending on density, negativity, and impact attributes; and (3) ... See full document
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Sentiment Analysis of Twitter Data
... Think of any product based company if they want to manufacture a mobile phone and they are not sure that it will make profit. They can do a quick analysis of market ,they can analyze latest trend in mobile phone ... See full document
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