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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Page: 1 2 3 4 5 6 Hits 81 – 100 of 103 81 Odi et Amo. Creating, Evaluating and Extending Sentiment Lexicons for Latin Sprugnoli, Rachele (orcid:0000-0001-6861-5595); Passarotti, Marco (orcid:0000-0002-9806-7187); Corbetta, Daniela. - : European Language Resources Association (ELRA), 2020. : country:FRA, 2020. : place:Paris, 2020 BASE Show details 82 MultiEmotions-it: A new dataset for opinion polarity and emotion analysis for Italian Sprugnoli, R. (orcid:0000-0001-6861-5595). - : Accademia University Press, 2020. : country:ITA, 2020. : place:Torino, 2020 BASE Show details 83 Techniques for improving the labelling process of sentiment analysis in the Saudi stock market AL-Rubaiee, Hamed Saad; Qiu, Renxi; Alomar, Khalid. - : Science and Information Organization, 2020 BASE Show details 84 Analysis of the relationship between Saudi twitter posts and the Saudi stock market AL-Rubaiee, Hamed Saad; Qiu, Renxi; Li, Dayou. - : Institute of Electrical and Electronics Engineers Inc., 2020 BASE Show details 85 Identifying Mubasher software products through sentiment analysis of Arabic tweets AL-Rubaiee, Hamed Saad; Qiu, Renxi; Li, Dayou. - : Institute of Electrical and Electronics Engineers Inc., 2020 BASE Show details 86 Visualising Arabic sentiments and association rules in financial text AL-Rubaiee, Hamed Saad; Qiu, Renxi; Li, Dayou. - : SAI, 2020 BASE Show details 87 Using Multi-granular Fuzzy Linguistic Modelling Methods to Represent Social Networks Related Information in an Organized Way Morente Molinera, Juan Antonio; Cabrerizo, F.J.; Alonso, S.. - : Universitatea Agora, 2020 BASE Show details 88 Arabic-English Google Translation Evaluation and Arabic Sentiment Analysis Aizouky, Zeina. - : University of Alberta. Digital Humanities., 2020 Abstract: Degree: Master of Arts ; Abstract: Machine translation is one of the most important tasks in the automatic processing of the natural languages, but its systems are still very far from achieving any performance close to ideal human translation due to many obstacles and difficulties. For example, grammatical rules between different languages are different, also, some words in the source language may not have an equivalent translation in the target language and this will lead to accurate translation results. Also, sentiment analysis is another application of Natural Language Processing (NLP) which is the process of identifying the feelings or sentiments held in a piece of text and classifying them into positive, negative, or neutral. This study sets out to examine the efficiency and accuracy of Google Translate’s translation between the Arabic and English languages and to evaluate the qualification of sentiment analysis when we apply it to Arabic texts. My study will also examine how old texts and texts written in dialects of Arabic affect both sentiment analysis and Google Translate’s performance. So, I used Arabic songs’ lyrics which differ between each other in terms of precedence and formality where they can be old or new, and formal or informal. To evaluate the results of Google Translate in this thesis, a lexical and grammatical analysis was used and the retrieval rate of words, sentences, and meanings of the text in the source language was calculated. In this thesis, I proposed a new approach to sentiment analysis which I conducted over five Arabic songs’ lyrics. Some of the lyrics are written in informal colloquial Arabic and some in Modern Standard Arabic (MSA). I performed sentiment analysis on those lyrics to evaluate the efficiency of the Google translation by comparing the results of the sentiment analysis of Arabic lyrics and the translated versions of those lyrics. The results of the evaluation of Google Translate showed that Google Translate has failed to achieve adequate translation, especially in old complex informal and unstructured Arabic texts. In addition, the results of applying sentiment analysis to Arabic texts showed that old and informal texts lower the performance of sentiment analysis. Also, applying English sentiment analysis to the translated version gave different results than applying Arabic opinion mining to the Arabic original version. Furthermore, Google Translate lowered the accuracy of the English sentiment analysis compared to the results I got when I applied the English sentiment analysis to my suggested translation of the lyrics. Keyword: Arabic Sentiment Analysis; Arabic-English Translation; Google Translation URL: https://era.library.ualberta.ca/items/55622b1e-bed3-4260-ad86-042408dff84d https://doi.org/10.7939/r3-mbh7-0x08 BASE Hide details 89 English Studies and Literary Education in the Era of Media Manipulation: Context, Perceptions, Feelings and Challenges Caballero Aceituno, Yolanda; Orrequia-Barea, Aroa. - : Universidad de Alicante. Departamento de Filología Inglesa, 2020 BASE Show details 90 Predicting Students’ College Drop Out and Departure Decisions by Analyzing their Campus-Based Social Network Text Messages Allen, Rebecca; Nakonechnyi, Alex; Seidmann, Abraham. - 2020 BASE Show details 91 A Study on the Contributions of Domain-Specific Semantics Towards Aspect-Based Sentiment Analysis Mokadam, Aashay In: Master's Theses (2020) BASE Show details 92 Sentiment Analysis of Textual Content in Social Networks. From Hand-Crafted to Deep Learning-Based Models Jabreel, Mohammed Hamood Abdullah. - : Universitat Rovira i Virgili, 2020 In: TDX (Tesis Doctorals en Xarxa) (2020) BASE Show details 93 Towards Arabic textual and multi-modal sentiment analysis Alqarafi, Abdulrahman. - : University of Stirling, 2020 BASE Show details 94 This video is sponsored : text and sentiment analysis of YouTube health-related vlog comments and brand endorsement effectiveness Yang, Zihan, M.A.. - 2020 BASE Show details 95 Sentiment Lexicon Induction and Interpretable Multiple-instance Learning in Financial Markets Fu, Chengyao. - : University of Waterloo, 2020 BASE Show details 96 Exploring Explicit and Implicit Feature Spaces in Natural Language Processing Using Self-Enrichment and Vector Space Analysis Sippola, Vincent In: Electronic Thesis and Dissertation Repository (2020) BASE Show details 97 Towards Subjective Multimedia Summarization Framework for Sporting Event in the Context of Digital Twins Aloufi, Samah Bader. - : Université d'Ottawa / University of Ottawa, 2020 BASE Show details 98 Domain specific lexicon generation through sentiment analysis Shaukat, Kamran; Hameed, Ibrahim A.; Luo, Suhuai. - : International Association of Online Engineering (IAOE), 2020 BASE Show details 99 Using Keystroke Dynamics in a Multi-Agent System for User Guiding in Online Social Networks Aguado-Sarrió, Guillem; Julian Inglada, Vicente Javier; García-Fornes, A. - : MDPI AG, 2020 BASE Show details 100 A Twitter Political Corpus of the 2019 10N Spanish Election Rosso, Paolo; Ponzetto, Simone Paolo; Sánchez-Junquera, Javier. - : Springer, 2020 BASE Show details Page: 1 2 3 4 5 6

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