Twitter is becoming an increasingly popular platform used by financial analysts to monitor and forecast financial markets. In this paper we investigate the impact of the sentiments expressed in Twitter on the subsequent market movement, specifically the bitcoin exchange rate. This study is divided into two phases, the first phase is sentiment analysis, and the second phase is correlation and regression. We analyzed tweets associated with the Bitcoin in order to determine if the user’s sentiment contained within those tweets reflects the exchange rate of the currency. The sentiment of users over a 2-month period is classified as having a positive or negative sentiment of the digital currency using the proposed CNN-LSTM deep learning model. By applying Pearson's correlation, we found that the sentiment of the day (d) had a positive effect on the future Bitcoin returns on the next day (d+1). The prediction accuracy of the linear regression model for the next day's revenue was 78%.
This research aims to clarify the conceptual framework of social entrepreneurship shows the importance of the development of social entrepreneurship according to the contextual aspects and the social value achieved from these works. It also identifies the degree of level of a sample of women entrepreneurs in Iraq for the extent of the relationship between social entrepreneurship and women's empowerment. It also explains the impact of entrepreneurial work in empowering women and the extent to which there are individual differences between the average scores of the sample members’ estimation of the level of social entrepreneurship according to social status, age group, educational qualification, and specialization according to the s
... Show MoreThe aim of this research is to identify how to employ the social imagination and its representations in the paintings of the students of the Department of Art Education. Students of the Department of Art Education in the light of this tool, and the researcher reached a number of results, the most important of which are:
1. The indicator of the social imagination in the excitement of the artist and the recipient, because the representations are embodied in forms within the painting and close to reality.
2. An artistic sample of the representational imagination and the creative imagination was found to be more than the imaginary imagination.
3. Individual symptoms related to the term.
4. The representations of the socia
In a report by Transparency Organization in 2010, Iraq has 200 newspapers, magazines, sixty-seven radio stations and 45 satellite TV channels. The increase in these figures is measured in days or weeks and not months and years. This fact confirms the importance of studying content providers, especially youth sports content, for two reasons: the first is that young people constitute the highest percentage in Iraqi society, with all the potential involved in shaping the future aspects; the second reason is that for years sport has become an important pillar in people's lives not only in the entertainment aspect as it was seen in the past; Rather, sport has an influential presence in politi
... Show MoreThe present paper aims at investigating the linguistic image portrayed by UNICEF reports on the Iraqi child from a critical discourse analysis perspective during Covid19 pandemic (2020). The paper attempts to fill a gap in research literature concerning the linguistic construction of the Iraqi child by the UNICEF reports during the critical health crisis of Covid19. Van Leeuwen’s (2008) approach of social actor representation has been adopted for this purpose. From Van Leeuwen’s approach, the category of determination (single determination and overdetermination) has been selected to be the main analytical tool for its high compatibility with the set of objectives put forward to figure out how such a globally effective and
... Show MoreThe morphometric parameters of Acinopus (Acinopus) laevigatus Ménétriés, 1832 (Coleoptera, Carabidae) were studied and their altitudinal variability was assessed. The length of head is the most variable, and the smallest value of the coefficient of variation is observed for the width of elytra. The length of body parts (head, pronotum, elytra) were more variable compared to their width. The correlation relationship between the morphometric parameters of different parts of the body was analyzed. A high correlation was found between the elytra length (EL) and the total body length (BL) (r=0.93), and the lowest correlation was found between the elytra width (EW) and the pronotum length (PL) (r=0.57). According to all measurement indicato
... Show MoreThe successive international changes in the economic, political, cultural and other fields resulted in many phenomena that occupied different levels of interest, and have been followed up, studied and analysed by specialists and researchers especially under the development of the media in the global communication.
Even though these phenomena had reflections in the communication domain like development and changes in the mechanism of behaviours between the international communities, they created in the meantime a phenomenon that caused an imbalance in the production, spread and the use of the informations that were supposed to be for fewer than 5 countries whereas it actually it is for more than 180 countries.
This research aims at identifying the commitment of satellite news channels in Arabic to the set of important standards that reflect their credibility in dealing with the media material, and considering that these channels give special importance to events in Iraq, as well as the Arab region and the world, decide to choose them and study them with a problem The research was a question about the level of credibility of Iraqi media. This research is descriptive research, which used the survey method on an objective sample of 245 items, while the questionnaire was used as a data collection tool. Seven channels were selected in Arabic for the study. The three most watched channels were chosen. These channels included the channels of Russia t
... Show MoreImitation learning is an effective method for training an autonomous agent to accomplish a task by imitating expert behaviors in their demonstrations. However, traditional imitation learning methods require a large number of expert demonstrations in order to learn a complex behavior. Such a disadvantage has limited the potential of imitation learning in complex tasks where the expert demonstrations are not sufficient. In order to address the problem, we propose a Generative Adversarial Network-based model which is designed to learn optimal policies using only a single demonstration. The proposed model is evaluated on two simulated tasks in comparison with other methods. The results show that our proposed model is capable of completing co
... Show MoreDuring COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve
... Show MoreWith the rapid development of smart devices, people's lives have become easier, especially for visually disabled or special-needs people. The new achievements in the fields of machine learning and deep learning let people identify and recognise the surrounding environment. In this study, the efficiency and high performance of deep learning architecture are used to build an image classification system in both indoor and outdoor environments. The proposed methodology starts with collecting two datasets (indoor and outdoor) from different separate datasets. In the second step, the collected dataset is split into training, validation, and test sets. The pre-trained GoogleNet and MobileNet-V2 models are trained using the indoor and outdoor se
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