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Sentiment Analysis in Social Media using Machine Learning Techniques
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Over the last period, social media achieved a widespread use worldwide where the statistics indicate that more than three billion people are on social media, leading to large quantities of data online. To analyze these large quantities of data, a special classification method known as sentiment analysis, is used. This paper presents a new sentiment analysis system based on machine learning techniques, which aims to create a process to extract the polarity from social media texts. By using machine learning techniques, sentiment analysis achieved a great success around the world. This paper investigates this topic and proposes a sentiment analysis system built on Bayesian Rough Decision Tree (BRDT) algorithm. The experimental results show the success of this system where the accuracy of the system is more than 95% on social media data.

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Publication Date
Mon Oct 01 2012
Journal Name
Al–bahith Al–a'alami
The Role of Social Media in Changing Media
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Media theories and studies have provided many diligences on the concept of social media and the circle of influence, including the theory of social marketing which deals with how to promote ideas espoused by the elite in a society to become a recognized social value. The emergence of social networks provided a revolutionary breakthrough, taking the media to unprecedented horizons; and giving its users great opportunities to influence and move across borders without restrictions and censorship, except in a relatively limited manner.

So, the emergence of social media has created channels of live broadcasting from its audience in a method of development that changes the essence of the known communication theories; a

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Publication Date
Mon Oct 01 2012
Journal Name
Albahith Alalami
The Role of Social Media in Changing Media
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Media theories and studies have provided many diligences on the concept of social media and the circle of influence, including the theory of social marketing which deals with how to promote ideas espoused by the elite in a society to become a recognized social value. The emergence of social networks provided a revolutionary breakthrough, taking the media to unprecedented horizons; and giving its users great opportunities to influence and move across borders without restrictions and censorship, except in a relatively limited manner. So, the emergence of social media has created channels of live broadcasting from its audience in a method of development that changes the essence of the known communication theories; and stops the monopoly of th

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Publication Date
Wed Jul 20 2022
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
A Scoping Review of Machine Learning Techniques and Their Utilisation in Predicting Heart Diseases
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Heart diseases are diverse, common, and dangerous diseases that affect the heart's function. They appear as a result of genetic factors or unhealthy practices. Furthermore, they are the leading cause of mortalities in the world. Cardiovascular diseases seriously concern the health and activity of the heart by narrowing the arteries and reducing the amount of blood received by the heart, which leads to high blood pressure and high cholesterol. In addition, healthcare workers and physicians need intelligent technologies that help them analyze and predict based on patients’ data for early detection of heart diseases to find the appropriate treatment for them because these diseases appear on the patient without pain or noticeable symptoms,

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Sentiment Analysis on Roman Urdu Students’ Feedback Using Enhanced Word Embedding Technique
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Students’ feedback is crucial for educational institutions to assess the performance of their teachers, most opinions are expressed in their native language, especially for people in south Asian regions. In Pakistan, people use Roman Urdu to express their reviews, and this applied in the education domain where students used Roman Urdu to express their feedback. It is very time-consuming and labor-intensive process to handle qualitative opinions manually. Additionally, it can be difficult to determine sentence semantics in a text that is written in a colloquial style like Roman Urdu. This study proposes an enhanced word embedding technique and investigates the neural word Embedding (Word2Vec and Glove) to determine which perfo

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Publication Date
Sat Jan 01 2022
Journal Name
Turkish Journal Of Physiotherapy And Rehabilitation
classification coco dataset using machine learning algorithms
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In this paper, we used four classification methods to classify objects and compareamong these methods, these are K Nearest Neighbor's (KNN), Stochastic Gradient Descentlearning (SGD), Logistic Regression Algorithm(LR), and Multi-Layer Perceptron (MLP). Weused MCOCO dataset for classification and detection the objects, these dataset image wererandomly divided into training and testing datasets at a ratio of 7:3, respectively. In randomlyselect training and testing dataset images, converted the color images to the gray level, thenenhancement these gray images using the histogram equalization method, resize (20 x 20) fordataset image. Principal component analysis (PCA) was used for feature extraction, andfinally apply four classification metho

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Publication Date
Sat Jun 27 2020
Journal Name
Iraqi Journal Of Science
The Performance Differences between Using Recurrent Neural Networks and Feedforward Neural Network in Sentiment Analysis Problem
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 With the spread use of internet, especially the web of social media, an unusual quantity of information is found that includes a number of study fields such as psychology, entertainment, sociology, business, news, politics, and other cultural fields of nations. Data mining methodologies that deal with social media allows producing enjoyable scene on the human behaviour and interaction. This paper demonstrates the application and precision of sentiment analysis using traditional feedforward and two of recurrent neural networks (gated recurrent unit (GRU) and long short term memory (LSTM)) to find the differences between them. In order to test the system’s performance, a set of tests is applied on two public datasets. The firs

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Publication Date
Sat Dec 30 2023
Journal Name
Iraqi Journal Of Science
Proposed Security Models for Node-level and Network-level Aspects of Wireless Sensor Networks Using Machine Learning Techniques
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     As a result of the pandemic crisis and the shift to digitization, cyber-attacks are at an all-time high in the modern day despite good technological advancement. The use of wireless sensor networks (WSNs) is an indicator of technical advancement in most industries. For the safe transfer of data, security objectives such as confidentiality, integrity, and availability must be maintained. The security features of WSN are split into node level and network level. For the node level, a proactive strategy using deep learning /machine learning techniques is suggested. The primary benefit of this proactive approach is that it foresees the cyber-attack before it is launched, allowing for damage mitigation. A cryptography algorithm is put

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Publication Date
Thu Jun 01 2023
Journal Name
Ifip Advances In Information And Communication Technology
Rapid Thrombogenesis Prediction in Covid-19 Patients Using Machine Learning
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Machine Learning (ML) algorithms are increasingly being utilized in the medical field to manage and diagnose diseases, leading to improved patient treatment and disease management. Several recent studies have found that Covid-19 patients have a higher incidence of blood clots, and understanding the pathological pathways that lead to blood clot formation (thrombogenesis) is critical. Current methods of reporting thrombogenesis-related fluid dynamic metrics for patient-specific anatomies are based on computational fluid dynamics (CFD) analysis, which can take weeks to months for a single patient. In this paper, we propose a ML-based method for rapid thrombogenesis prediction in the carotid artery of Covid-19 patients. Our proposed system aims

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Publication Date
Mon Jan 01 2024
Journal Name
Lecture Notes In Networks And Systems
Using Machine Learning to Control Congestion in SDN: A Review
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Publication Date
Sat Apr 01 2017
Journal Name
Al–bahith Al–a'alami
Privacy Violation in Social Media Sites
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Technological superiority of the means of communication and media has allowed these methods to dominate and are replaced by alternative positon of traditional media. The internet with its advantages and benefits benefited in various areas of life, especially media and achieve what no previous technology could achieve and any technology what comes after it can't be isolated from the internet. Today, the internet is the cornerstone of communication and connection in the world and the most important means of public and personal communication at the same time. The interactive feature of the internet and the cancelation of space and time restrictions create a new media that allowed everyone to express what they wanted freely. The internet app

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