Sentiment analysis refers to the task of identifying polarity of positive and negative for particular text that yield an opinion. Arabic language has been expanded dramatically in the last decade especially with the emergence of social websites (e.g. Twitter, Facebook, etc.). Several studies addressed sentiment analysis for Arabic language using various techniques. The most efficient techniques according to the literature were the machine learning due to their capabilities to build a training model. Yet, there is still issues facing the Arabic sentiment analysis using machine learning techniques. Such issues are related to employing robust features that have the ability to discriminate the polarity of sentiments. This paper proposes a hybrid method of linguistic and statistical features along with classification methods for Arabic sentiment analysis. Linguistic features contains stemming and POS tagging, while statistical contains the TF-IDF. A benchmark dataset of Arabic tweets have been used in the experiments. In addition, three classifiers have been utilized including SVM, KNN and ME. Results showed that SVM has outperformed the other classifiers by obtaining an f-score of 72.15%. This indicates the usefulness of using SVM with the proposed hybrid features.
Resumen:
La traducción de los dos verbos ser y estar no es una tarea tan simple como piensan muchas personas, sino es una de las complicadas y difíciles tareas, ya que el traductor tiene que saber y perfeccionar los correctos casos gramaticales relacionados con esos dos verbos auxiliares tanto el verbo ser como el verbo estar, especialmente en la frase nominal para que pueda dar una clara y correcta traducción. Usados con el mismo adjetivo, "ser" comunicará una cualidad que es parte de la identidad o naturaleza del sujeto, mientras que "estar" comunicará un estado o circunstancia del mismo. Este e
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Modification of gas chromatographic technique for the separation and determination of methyl ethoy silane compounds which were synthesized by the addition of absolute ethanol to methyl chlorosilane compounds have been elaborated experimentally. The addition of absolute dry ethanol to methyl chlorosilane compounds in the presence of a dry stream of nitrogen gas led to sweep out the liberated HCl gas. This method was found to be the suitable method for the preparation of methyl ethoxy silane compounds. The optimum parameter selected after careful and precise studies was between 20 – 30 ml \ min to carrieir gas flow rate, while applied temperatures of detector and injection part were 250 Â
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