Language is essential for politics, for producing, disseminating, engaging with, and reacting to political discourse. The pragmatics of political speeches is crucial to the development of effective political communication tactics. Thus, speech is situated at the intersection of rhetoric, linguistics, and politics. In communication, intent is a pragmatic factor that plays a crucial role at the time of the communication process. Speech is of paramount importance to the social and political domains. Through the use of concepts and the relationship between language and politics, the study analyzes the function of language in communication and interpretation of intentions. The study of the relationships between language and the situations in which it is employed is the focus of the subfield of linguistics known as pragmatics. Politicians communicate directly with the public to persuade them to support their plans or beliefs. In this area, certain concepts of pragmatics can be applicable to the analysis of the political speeches demonstrates that political leaders conduct a variety of acts through their speeches. This article discusses the concept of Relation between Pragmatics and Politics, derived from its two basic components throughout linguistic concept. The authors attempt to identify elements or factors that interweave these two apparently separate spheres, by highlighting all the pragmatic concepts that can be included in the analysis of political discourses. In addition to giving an overview of the concept of political speeches and their relationship to the theory of pragmatism through the principle of analyzing the intentions of the politicians.
Most companies use social media data for business. Sentiment analysis automatically gathers analyses and summarizes this type of data. Managing unstructured social media data is difficult. Noisy data is a challenge to sentiment analysis. Since over 50% of the sentiment analysis process is data pre-processing, processing big social media data is challenging too. If pre-processing is carried out correctly, data accuracy may improve. Also, sentiment analysis workflow is highly dependent. Because no pre-processing technique works well in all situations or with all data sources, choosing the most important ones is crucial. Prioritization is an excellent technique for choosing the most important ones. As one of many Multi-Criteria Decision Mak
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Sentiment analysis is one of the major fields in natural language processing whose main task is to extract sentiments, opinions, attitudes, and emotions from a subjective text. And for its importance in decision making and in people's trust with reviews on web sites, there are many academic researches to address sentiment analysis problems. Deep Learning (DL) is a powerful Machine Learning (ML) technique that has emerged with its ability of feature representation and differentiating data, leading to state-of-the-art prediction results. In recent years, DL has been widely used in sentiment analysis, however, there is scarce in its implementation in the Arabic language field. Most of the previous researches address other l
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Multivariate Non-Parametric control charts were used to monitoring the data that generated by using the simulation, whether they are within control limits or not. Since that non-parametric methods do not require any assumptions about the distribution of the data. This research aims to apply the multivariate non-parametric quality control methods, which are Multivariate Wilcoxon Signed-Rank ( ) , kernel principal component analysis (KPCA) and k-nearest neighbor ( −
Coaches and analysts face a significant challenge of inaccurate estimation when analyzing Men's 100 Meter Sprint Performance, particularly when there is limited data available. This necessitates the use of modern technologies to address the problem of inaccurate estimation. Unfortunately, current methods used to estimate Men's 100 Meter Sprint Performance indexes in Iraq are ineffective, highlighting the need to adopt new and advanced technologies that are fast, accurate, and flexible. Therefore, the objective of this study was to utilize an advanced method known as artificial neural networks to estimate four key indexes: Accelerate First of 10 meters, Speed Rate, Time First of 10 meters, and Reaction Time. The application of artifi
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