![]() In this thesis, I proposed a new approach to sentiment analysis which I conducted over five Arabic songs’ lyrics. 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. 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. My study will also examine how old texts and texts written in dialects of Arabic affect both sentiment analysis and Google Translate’s performance. 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. 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. ![]() 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. 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. Arabic-English Google Translation Evaluation and Arabic Sentiment Analysis ![]()
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