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The sustainable development goal 4 (SDG4) aims to “ensure inclusive and equitable quality education and promote lifelong learning opportunities for all”, Therefore., researchers are inspired to study the fairness and equality in different... more
The sustainable development goal 4 (SDG4) aims to “ensure inclusive and equitable quality education and promote lifelong learning opportunities for all”, Therefore., researchers are inspired to study the fairness and equality in different aspects of education. Some studies are focused on social and academic initiatives and others on developing state-of-the-art technology to enhance the education between students equally. Henceforth., in this paper a novel affordable chatbot implemented by using a neural network model and natural language processing (NLP) to assist students in high schools particularly., since high school is one of the most essential stages in students” lives., as in this stage., students have the option to select their academic streams and advanced courses that can shape their career with their passions and interests. The dataset in this study collected from different academic resources such as schools & universities websites., schools” advisers., parents and students. It includes (968) pairs of enquiries and tags. The first column represents the student's enquiry; the second column indicates the tag or the class of each sentence. The model built by connecting the input data into embedding layer., and then the data fed into the LSTM layer with different number of neurons., then authors used sigmoid function for the output layer. The result in this study shows that the performance of the chatbot is improved by increasing the number of neurons from 5 to 8, the model achieved high accuracy ratio with score (96.5 % ). In future the model will be developed with stacked LSTM layers with using softmax activation function in the output layer, as different classes will be added as well in the dataset.
The various types of social media were increased rapidly, as people’s need to share knowledge between others. In fact, there are various types of social media apps and platforms such as Facebook, Twitter, Reddit, Instagram, and others.... more
The various types of social media were increased rapidly, as people’s need to share knowledge between others. In fact, there are various types of social media apps and platforms such as Facebook, Twitter, Reddit, Instagram, and others. Twitter remains one of the most popular social application that people use for sharing their emotional states. However, this has increased particularly during the COVID-19 pandemic. In this paper, we proposed a chatbot for evaluating the sentiment analysis by using machine learning algorithms. The authors used a dataset of tweets from Kaggle’s website, and that includes 41157 tweets that are related to the COVID-19. These tweets were classified and labelled to four categories: Extremely positive, positive, neutral, negative, and extremely negative. In this study, we applied Machine Learning algorithms, Support Vector Machines (SVM), and the Naïve Bayes (NB) algorithms and accordingly, we compared the accuracy between them. In addition to that, the cla...
Research on tools for automating the proofreading of Arabic text has received much attention in recent years. There is an increasing demand for applications that can detect and correct Arabic spelling and grammatical errors to improve the... more
Research on tools for automating the proofreading of Arabic text has received much attention in recent years. There is an increasing demand for applications that can detect and correct Arabic spelling and grammatical errors to improve the quality of Arabic text content and application input. Our review of previous studies indicates that few Arabic spell-checking research efforts appropriately address the detection and correction of ill-formed words that do not conform to the Arabic morphology system. Even fewer systems address the detection and correction of erroneous well-formed Arabic words that are either contextually or semantically inconsistent within the text. We introduce an approach that investigates employing deep neural network technology for error detection in Arabic text. We have developed a systematic framework for spelling and grammar error detection, as well as correction at the word level, based on a bidirectional long short-term memory mechanism and word embedding, ...
The case study implements an ERP integration system on a local ceramic company system specifically for Quality Management. This report will cover the basic operation of the ceramic. After introducing the ceramic production scheme, we scan... more
The case study implements an ERP integration system on a local ceramic company system specifically for Quality Management. This report will cover the basic operation of the ceramic. After introducing the ceramic production scheme, we scan a total of 7 papers on ERP system implementation analysis in different fields. Two of them will be represented in our case study, which covers one side of the production process. The first paper proposes a new schedule scheme for a Spanish tile company. The second case study paper is on improving the quality management of new products. After that, we will identify the problem faced in the company and analyze the current situation. The major problems were stated in the report, which includes controlling the department's interaction, the finance requirement of the company, material management, and quality management. After stating and analyzing the major problems, we will identify and evaluate three ERP integration platform solutions: SAP ERP, NetSuite, and Sage. We chose an SAP platform to implement after a discussion with their top management team. Then we provided a detailed company process and important setting to be adapt SAP to company needs. We concluded the case study by addressing the list of improvements to the company in the case of SAP implementation.
As the number of university students using social media increases, the interest in assessing the adoption of social media applications and the factors encouraging it whether inside or outside classrooms has also risen. Nevertheless,... more
As the number of university students using social media increases, the interest in assessing the adoption of social media applications and the factors encouraging it whether inside or outside classrooms has also risen. Nevertheless, evaluating the educational outcomes of integrating social media in the university teaching has not been researched sufficiently. Therefore, this study aims at exploring these educational outcomes and assessing a research model of antecedents and the cost of social media use. It also determines the factors of implementing social networking media for e-learning in the United Arab Emirates higher education institutions utilizing the Technology Acceptance Model (TAM) which stresses the Perceived Ease of Use and Perceived Usefulness along with the Behavior Intention to use social networking media. The quantitative response of 408 university students embedding social media in their teaching methods was analyzed. To predict an Emirati student’s behavioral inten...
Lately, instructors, as well as learners, have been integrating social networking media in the context of higher education systems. Social networking media has also become the subject of interest for researchers to explore its impacts in... more
Lately, instructors, as well as learners, have been integrating social networking media in the context of higher education systems. Social networking media has also become the subject of interest for researchers to explore its impacts in the process of imparting and acquiring higher education. Various platforms have been introduced by the social networking media to facilitate the process of communication between the teachers and students while it eases creating and sharing for its users. Through conducting research on the dynamics of students and instructors, their acceptance regarding the various innovations and their attitude towards these platforms, useful modifications of the current approaches can be done accordingly in a way that ensures a wide adaptation of the software. The current study is built on the ground of established research termed the Unified Theory of Acceptance and Use of Technology (UTAUT). The findings of this research are employed to confirm the factors of uti...
Customs administration oversees the important processes of facilitating trade and protecting local societies and economies: the former by minimising shipment processing times and the latter by ensuring the lawfulness of trade. One of the... more
Customs administration oversees the important processes of facilitating trade and protecting local societies and economies: the former by minimising shipment processing times and the latter by ensuring the lawfulness of trade. One of the main processes that affect the facilitation and protection of trade is the risk of the shipment assessment process. This assessment is performed by analysing available information about shipments to determine whether or not they require physical inspection. When a shipment is identified as suspicious, a physical inspection that can take hours is performed to identify and (dis)confirm the risk factors. In this process, changing trading behaviour by increasing the volume of expected shipments can be a source of pressure. This work proposes a secondary distributed risk assessment method that provides customs administration with an online risk assessment capabilities. The proposed method complements the risk assessments performed at customs administrati...
As part of the international trade supply chain, Dubai Customs acts as the gatekeeper, protecting the society and the economy. During the exportation process, one of the primary responsibilities of the Customs Authority is to authenticate... more
As part of the international trade supply chain, Dubai Customs acts as the gatekeeper, protecting the society and the economy. During the exportation process, one of the primary responsibilities of the Customs Authority is to authenticate the documents submitted with the exportation declaration application, to ensure the legality of the trade. Due to the lack of direct communication channel among the exportation supply chain participants, authenticating the exportation application documents is a time-consuming and challenging task. Typically, there is no direct communication paradigm among the supply chain participants. Therefore, in most cases, the authenticating process relies on human judgment. This increases the chance of non-detection of fraudulent exportation documents. In this regard, the redesign of the exportation supply chain to automate the authentication process has become an essential requirement. This paper addresses this requirement by proposing a blockchain-based sys...
Sentiment analysis (SA) is one of the most emerging field of study in natural language processing (NLP) domain that primarily focuses on the opinion extortion of people’s lingual and penned articulation. Considerable number of studies... more
Sentiment analysis (SA) is one of the most emerging field of study in natural language processing (NLP) domain that primarily focuses on the opinion extortion of people’s lingual and penned articulation. Considerable number of studies about sentiment analysis over Arabic language are probed to label its polarity into positive or negative since this becomes very common dialect to Arabian internet users to depict their views. The prime understanding of this systematic review over Arabic sentiment analysis gives an insight about the classic, modern and colloquial flavors of its high morphological richness. Potential documents were filtered from different data sources published from 2015 to 2020 as well relevant 10 research articles were analyzed carefully and findings were captured based on the questionnaires framed with methods used for data selection and approached algorithms. The key finding is that 89% of the analyzed sample resulted in positive outcomes. Positively research papers that originated from the Kingdom of Saudi Arabia has contributed to the above said achievement. In this aspect, this study is an initiative to demonstrate and detail the progressive advancement made in Arabic NLP based SA processing, eventually this work can suffice as an essential reference especially a clear insight about the polarity of the Arabic words used in the social media conversation to researchers of natural language processing domain.
Text and content mining are the subcategory of data mining. This category of data mining is used to extract the information from web or web pages of a website. This mining identifies useful information from web content like web pages,... more
Text and content mining are the subcategory of data mining. This category of data mining is used to extract the information from web or web pages of a website. This mining identifies useful information from web content like web pages, search logs, and other website-related content. The extracted information can be used in many applications, for example, we can extract opinions from online sources and web hierarchy which provides better insights and knowledge. In this paper, we conducted a systematic review that included 18 research papers that are relevant to the topic and matches the inclusion criteria of this study. From these research papers we were able to answer the research questions that we identified. The questions are related to the applications, techniques and issues of the text and web mining. The findings suggest that many research papers made a good foundation for this topic, and gave an informative explanation of each type of techniques used in text and web mining, as well as some issues that can be a future work for researchers who are interested in the topic.
Learning analytics has emerged as a new domain for identifying students’ behaviors, academic performance, academic achievement, and other related learning issues. Given its paramount importance and recency, several review studies were... more
Learning analytics has emerged as a new domain for identifying students’ behaviors, academic performance, academic achievement, and other related learning issues. Given its paramount importance and recency, several review studies were conducted. However, the previous reviews have mainly focused on the behavioral, affective, cognitive, and metacognitive patterns of learning. It has been observed that the existing reviews neglected to review the learning analytics studies from the lenses of their categories. Therefore, this review sheds the light on analyzing 19 articles published on learning analytics by classifying them into five different categories, including prediction model, learning theory, designed framework, applications, and data-driven decision-making. Under each category, we present a summary of the respective research, its purpose, which dataset was used, how it was sourced, its algorithms, results, and further suggestions and recommendations. This review also tackles the main concepts, including big data, learning analytics, educational data mining, and technology acceptance. Critical remarks and research gaps were also discussed. It is believed that this review will provide an insight into the current research trends in learning analytics and serve as a source for pursuing further research in the domain.
Healthcare is considered a pillar for keeping humans alive, thus managing their health through diagnosing and treating the disease or illness is a must, in addition to preventing it. Knowledge management (KM) in healthcare domain plays a... more
Healthcare is considered a pillar for keeping humans alive, thus managing their health through diagnosing and treating the disease or illness is a must, in addition to preventing it. Knowledge management (KM) in healthcare domain plays a substantial role in the implementation of different processes to ensure the existence of good and outstanding healthcare systems. In this study, a systematic review is carried out among previous studies to observe KM processes studies with respect to healthcare. Based on a search strategy, the systematic review offers a broad analysis of 10 quality assessed research articles published in peer-reviewed journals from 2009 till 2019. The results provide findings regarding the most KM processes studied, which are knowledge sharing and applications, and the least KM processes studied, which are knowledge acquisition and protection. Surveys and interviews were used as research methods to avail information in the context of KM processes. Taiwan, Finland, United States, Ghana, and Pakistan were the most active countries in the surveyed studies. Furthermore, the contributors to these studies were healthcare staff. This review study attempts to determine and feature KM processes research as an increase considering healthcare systems.
Natural Language Processing (NLP) applications on real-life textual content require a suitable fit for purpose corpora, which can accommodate the ambiguity of the domain. Researchers in the field managed to synthesize gold-standard... more
Natural Language Processing (NLP) applications on real-life textual content require a suitable fit for purpose corpora, which can accommodate the ambiguity of the domain. Researchers in the field managed to synthesize gold-standard corpora in many domains and for varying tasks, assisted by domain experts and linguists. The wealth of information buried in free-text electronic documents in healthcare systems presents itself as a leading contender for NLP applications. In this literature review, the efforts to come up and utilize a clinically annotated corpus in a particular healthcare information extraction task are explored. Those efforts can be more pronounced when done on a new language with limited existing gold-standard clinical references. A great number of people around the globe interact with healthcare systems in languages other than English. Advancing the Clinical NLP research in their languages will propel the general progress in the field and potential healthcare advantages considerably. For the purposes of this review, we considered three major world languages: Spanish, Italian, and Chinese. This led to considering the research question to be about the viability of the creation or utilization of a gold-standard clinical corpus in a language other than English and how it can contribute in performing a complex clinical language mining task. The implementations reviewed in these languages considered varying approaches to overcome complexities in biomedical NLP in these languages. This study managed to highlight novel solutions to complex tasks and found that efforts in these languages can be highly successful if a non-English medical corpus is created from scratch, off-the-shelf tools are used or machine translation is considered to bridge the gap in biomedical NLP domain-specific lingual resources in these languages.
In the twenty-first century, with the evolution of Information Technology and Artificial Intelligence, Knowledge Management seems to be more advanced and sophisticated. Knowledge management has been studied and discussed for a long time... more
In the twenty-first century, with the evolution of Information Technology and Artificial Intelligence, Knowledge Management seems to be more advanced and sophisticated. Knowledge management has been studied and discussed for a long time by several researchers from academia and business sector due to its vitality for the success of organizations. Additionally, many leading companies around the world have adopted several knowledge management practices to ensure that they remain ahead of their rival companies in today’s competitive business world. Hence, companies continue to look for ways to improve these knowledge management practices. Several studies were conducted to have more profound understanding of the recent research trend of knowledge management processes and its best practices at organizations. However, this subject requires further investigation from other perspectives. Most of the previous studies neglect exploring the impact of applying artificial intelligence (AI) and information technology (IT) concepts and techniques on the efficiency of knowledge management at modern organizations in particular. This research systematically reviews and highlights the current knowledge management practices that have relied on IT and AI mechanisms and their impacts on modern organizations along with their challenges and limitations. The current research aims to provide a profound analysis of 15 (out of 844) research papers published in highly standard journals and conference proceedings throughout the past 10 years, from 2009 to 2019. This review study can be considered a pivotal reference for scholars as it fills in some gaps in knowledge management especially in IT and AI related studies.
Metaphor is a literary device that allows us to express a concept in terms of another. In other words, it is based on similarity between concepts. Metaphorical expressions represent a great variety and they are used in conventional... more
Metaphor is a literary device that allows us to express a concept in terms of another. In other words, it is based on similarity between concepts. Metaphorical expressions represent a great variety and they are used in conventional metaphors, which we reproduce and comprehend every day, poetic, novel, and Holy Qur’an. The use of metaphor is ubiquitous in natural language text and it is a serious bottleneck in automatic text understanding, and developing methods to identify and deal with metaphors is an open problem in Arabic natural language processing, especially Machine Translation. Due to the complexities involved in metaphor, it semantically influenced the meaning of machine-translated text. This makes metaphor an important research area for computational and cognitive linguistics, and its automatic identification and interpretation is indispensable for any semantics-oriented Arabic natural language processing. In this paper, we present the challenges of Arabic NLP of metaphors, which is very important in developing a computational NLP-based system for in Classical Arabic, Modern Standard Arabic and Dialect Arabic. We also highlight main problems that arises when translating an Arabic metaphor to another language.
It is widely acknowledged that knowledge management is critical to an organization's survival and growth. Every day, higher education institutions that are considered knowledge centers generate massive volumes of data. When this data... more
It is widely acknowledged that knowledge management is critical to an organization's survival and growth. Every day, higher education institutions that are considered knowledge centers generate massive volumes of data. When this data is analyzed using appropriate computational methods and technology, it can provide knowledge to improve organizational performance and students' academic experience. Healthcare organizations create massive volumes of data as a result of the usage of digital technologies to manage patient information and the organization's operations. When used successfully, this data aids in the creation of information that improves patient health and everyday organizational functioning, as well as the prevention of unfavorable public health scenarios such as the spread of infectious illnesses. This is where big data analytics comes in, providing rational methods for navigating enormous quantities of data to disclose knowledge that assists businesses and ana...
Cybersecurity procedures and policies are prevalent countermeasures for protecting organizations from cybercrimes and security incidents. Without considering human behaviors, implementing these countermeasures will remain useless.... more
Cybersecurity procedures and policies are prevalent countermeasures for protecting organizations from cybercrimes and security incidents. Without considering human behaviors, implementing these countermeasures will remain useless. Cybersecurity behavior has gained much attention in recent years. However, a systematic review that provides extensive insights into cybersecurity behavior through different technologies and services and covers various directions in large-scale research remains lacking. Therefore, this study retrieved and analyzed 2210 articles published on cybersecurity behavior. The retrieved articles were then thoroughly examined to meet the inclusion and exclusion criteria, in which 39 studies published between 2012 and 2021 were ultimately picked for further in-depth analysis. The main findings showed that the protection motivation theory (PMT) dominated the list of theories and models examining cybersecurity behavior. Cybersecurity behavior and intention behavior cou...
INTRODUCTION: An intent classification is a challenged task in Natural Language Processing (NLP) as we are asking the machine to understand our language by categorizing the users’ requests. As a result, the intent classification plays an... more
INTRODUCTION: An intent classification is a challenged task in Natural Language Processing (NLP) as we are asking the machine to understand our language by categorizing the users’ requests. As a result, the intent classification plays an essential role in having a chatbot conversation that understand students’ requests. OBJECTIVES: In this study, we developed a novel chatbot called “HSchatbot” for predicting the intent classifications from high school students’ enquiries. Evidently, students in high schools are the most concerned among all students about their future; thus, in this stage they need an instant support in order to prepare them to take the right decision for their career choice. METHODS: The authors in this study used the Multinomial Naive-Bayes and Random Forest classifiers for predicting the students’ enquiries, which in turn improved the performance of the classifiers by using the feature’s extractions. RESULTS: The results show that the random forest classifier perf...
Keyword extraction has gained increasing interest in the era of information explosion. The use of keyword extraction in documents context categorization, indexing and classification has led to the emphasis on graph-based keyword... more
Keyword extraction has gained increasing interest in the era of information explosion. The use of keyword extraction in documents context categorization, indexing and classification has led to the emphasis on graph-based keyword extraction. This research attempts to examine the impact of several factors on the result of using graph-based keyword extraction approach on a scientific dataset. This study applies a new model that processes the Medline scientific abstracts, produces graphs and extracts 3-graphlets and 4-graphlets from those graphs. The focus of the experiment is to come up with a dataset that consists of the keywords and their occurrences in the proposed graphlets patterns for each abstract with its class. Then, apply a supervised Naive Bayes classifier in order to assign a probability to each word, whether or not it is a keyword, and finally evaluate the performance of the graph-based keyword extraction approach. The model achieved significant results compared to the Term Frequency/Inverse Document Frequency (TF/IDF) baseline standard. The experimental results proved the capability of using graphs and graphlet patterns in keyword extraction tasks.
With the constant social, economic, and political changes witnessed in the world, numerous events occur in cities, and lead to important reactions from the public, including riots, civil disorder, and violent actions. During those events,... more
With the constant social, economic, and political changes witnessed in the world, numerous events occur in cities, and lead to important reactions from the public, including riots, civil disorder, and violent actions. During those events, situational awareness is crucial to gain a good understanding of the events and their impact on public opinion, which is typically difficult to measure. Opinion leaders are influential people who are able to shape the thoughts of others in the society, through eloquent and inspirational opinions and posts. Analyzing the sentiments of opinion leaders can give a strong indication about the sentiment in the street, due to the high influence that those leaders have on their followers. The purpose of this work is to build an opinion leaders’ sentiment monitoring framework that would serve as decision support tool for government officials. Our framework leverages our previously proposed opinion leader identification algorithm, along with text mining, text classification, and sentiment annotations to extract sentiment intelligence from opinion leaders’ posts, for effective analysis of public opinion about ongoing events. The proposed framework was implemented and tested using datasets collected from 27,000 Twitter accounts over a 15 months’ span. Opinion leaders were identified in five domains (economics, politics, health, sports, and education) based on their competency and popularity. Furthermore, a linear Support Vector Machine (SVM) classifier along with sentiment annotations were used to perform sentiment analysis on the tweets posted by 43 opinion leaders in relation to a major political event. The results obtained are very promising and indicate the potential of leveraging high impact social media content to gain insights about public opinion.
Social media plays a critical role in the public sector as it allows the government to interact with the citizens. With the United Arab Emirates being active on social media platforms, this study aims to identify the level of citizen... more
Social media plays a critical role in the public sector as it allows the government to interact with the citizens. With the United Arab Emirates being active on social media platforms, this study aims to identify the level of citizen engagement in Dubai government’s Twitter through the use of data mining techniques. Post engagement is the total number of citizens’ interactions with a tweet and can be measured using different tweet attributes including retweets, mentions, and likes. Moreover, this study investigates the impact of the twitter post characteristics on the citizens’ engagements level. Thus, we collected, prepared and processed 74,037 tweets that represents all tweets for Dubai government twitter accounts during 2018. These tasks were followed by statistical analyses of the impact of post characteristics on the citizens’ engagement level. Next, we implemented various machine learning models to evaluate the performance of using the post characteristics and post content to predict the engagement level of citizens. Results indicate that citizen engagement level in Dubai government’s Twitter is significantly impacted by all post characteristics. It is also revealed in the study that citizen engagement is higher during weekdays compared to weekends. Furthermore, the machine learning models achieved promising results to predict the citizens’ engagement with highest accuracy for Random Forest and Linear Support Vector Machine of 78.3% and 78.2% respectively.
The concept of using two neural networks to translate one Sequence to another sequence presented by google in 2014 has led to a revolutionary result of translation between the input sequence as source language and the output sequence as... more
The concept of using two neural networks to translate one Sequence to another sequence presented by google in 2014 has led to a revolutionary result of translation between the input sequence as source language and the output sequence as the target language. It overcomes the weakness of previous translation methods. On the other hand, C#.Net programming language becomes a widely-used programming language, as it is similar to the English language. Besides, it has a strong memory backup. However, it doesn't support other scientific functions like the sigmoid and tahn functions. This paper proposes an implementation of Sequence to Sequence algorithm using C#, and resolving the inability of C# in calculating the activation function by polynomial simplifying the sigmoid and tahn functions. Moreover, creating a small training and testing dataset using United Nation Arabic and English Letters from the official UN website as an approved translation source.
Recently, the usage of social media websites has become an attractive phenomenon in our daily life. These sites allow their users to communicate with each other through various tools. This results in learning and sharing of valuable... more
Recently, the usage of social media websites has become an attractive phenomenon in our daily life. These sites allow their users to communicate with each other through various tools. This results in learning and sharing of valuable information among their users. The nature of such information is categorized as unstructured and fuzzy text. The present study aims at analyzing textual data from Facebook and attempts to find interesting knowledge from such data and represent that knowledge in different forms. 33815 posts from 16 news channels pages over Facebook were extracted and analyzed. Findings revealed that there is a strong relationship between the Guardian and the Independent online news channels. Results indicated that there are four clusters in the study. Moreover, results showed that the overall collected data concentrated on three main topics: "Rio de Janeiro", "USA elections", and "UK leaves the European Union". These three main topics are con...
The integration of effective Knowledge Management (KM) in projects is founded on numerous factors. These factors include available resources, KM tools, leadership, organizational culture, and project objectives and goals among others. It... more
The integration of effective Knowledge Management (KM) in projects is founded on numerous factors. These factors include available resources, KM tools, leadership, organizational culture, and project objectives and goals among others. It is very important to set priorities for these considerations and factors in order to ensure effective KM integration into projects. Despite the fact that Project Knowledge Management (PKM) is characterized by numerous beneficial implications, it is also associated with risks. These risks include potential delays in project implementation and budget deficits. The Project Knowledge Management Life Cycle (PKMLC) includes five main stages: the knowledge creation, knowledge storage, knowledge dissemination, knowledge learning, and knowledge improvement. Each phase is essential towards the attainment of overall efficiency in the integration of KM into projects. Keywords: Knowledge Management (KM); Project Knowledge Management Life Cycle (PKMLC); Project K...
Sentiment analysis is not a new field of study and in research there has been focus on word polarity to distinguish between positive, negative, or neutral sentiments of words. However, the Emirati Dialect (and by extensi on the Arabian... more
Sentiment analysis is not a new field of study and in research there has been focus on word polarity to distinguish between positive, negative, or neutral sentiments of words. However, the Emirati Dialect (and by extensi on the Arabian Gulf dialects) had received little attention. This paper aims to provide a feasibility study of the possibility of assigning a sentiment value to a word when it comes to the UAE's Arabic Dialect (Emirati). In this study, ten keyword phrases were selected from the Emirati Dialect and were examined to assign their polarity from Twitter collections. During the course of this study and based on the statistical results of the  examination of the test sets, it became apparent that it was indeed possible to assign a sentiment value to certain Emirati words.

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