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Persian Sentence-level Sentiment Polarity Classification
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In: ICOTEN ; https://hal.archives-ouvertes.fr/hal-03258138 ; ICOTEN, Jun 2021, Glasgow, United Kingdom (2021)
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Persian Sentence-level Sentiment Polarity Classification
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In: ICOTEN ; https://hal.archives-ouvertes.fr/hal-03241928 ; ICOTEN, May 2021, Glasgow, France (2021)
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Extending persian sentiment lexicon with idiomatic expressions for sentiment analysis
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Abstract:
Nowadays, it is important for buyers to know other customer opinions to make informed decisions on buying a product or service. In addition, companies and organizations can exploit customer opinions to improve their products and services. However, the Quintilian bytes of the opinions generated every day cannot be manually read and summarized. Sentiment analysis and opinion mining techniques offer a solution to automatically classify and summarize user opinions. However, current sentiment analysis research is mostly focused on English, with much fewer resources available for other languages like Persian. In our previous work, we developed PerSent, a publicly available sentiment lexicon to facilitate lexicon-based sentiment analysis of texts in the Persian language. However, PerSent-based sentiment analysis approach fails to classify the real-world sentences consisting of idiomatic expressions. Therefore, in this paper, we describe an extension of the PerSent lexicon with more than 1000 idiomatic expressions, along with their polarity, and propose an algorithm to accurately classify Persian text. Comparative experimental results reveal the usefulness of the extended lexicon for sentiment analysis as compared to PerSent lexicon-based sentiment analysis as well as Persian-to-English translation-based approaches. The extended version of the lexicon will be made publicly available.
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URL: https://napier-surface.worktribe.com/2822974/1/Extending%20persian%20sentiment%20lexicon%20with%20idiomatic%20expressions%20for%20sentiment%20analysis http://researchrepository.napier.ac.uk/Output/2822974 https://doi.org/10.1007/s13278-021-00840-1
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Novel Deep Convolutional Neural Network-Based Contextual Recognition of Arabic Handwritten Scripts
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A novel context-aware multimodal framework for persian sentiment analysis
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A semi-supervised approach for sentiment analysis of arab (ic+ izi) messages: Application to the algerian dialect
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A Semi-supervised Approach for Sentiment Analysis of Arab(ic+izi) Messages: Application to the Algerian Dialect
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A Novel Context-Aware Multimodal Framework for Persian Sentiment Analysis
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Novel Deep Convolutional Neural Network-Based Contextual Recognition of Arabic Handwritten Scripts
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CochleaNet: A robust language-independent audio-visual model for real-time speech enhancement
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Offline Arabic Handwriting Recognition Using Deep Machine Learning: A Review of Recent Advances
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Deep Neural Network Driven Binaural Audio Visual Speech Separation
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Visual Speech In Real Noisy Environments (VISION): A Novel Benchmark Dataset and Deep Learning-Based Baseline System
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A hybrid Persian sentiment analysis framework: Integrating dependency grammar based rules and deep neural networks
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A Hybrid Persian Sentiment Analysis Framework: Integrating Dependency Grammar Based Rules and Deep Neural Networks ...
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Lip-reading driven deep learning approach for speech enhancement
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In: abs/1808.00046 ; 1 ; 10 (2019)
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A Hybrid Persian Sentiment Analysis Framework: Integrating Dependency Grammar Based Rules and Deep Neural Networks
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