Galimkair Mutanov, Vladislav Karyukin^*, Zhanl Mamykova

CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 913-930, 2021, DOI:10.32604/cmc.2021.017827

Abstract The volume of social media data on the Internet is constantly growing. This has created a substantial research field for data analysts. The diversity of articles, posts, and comments on news websites and social networks astonishes imagination. Nevertheless, most researchers focus on posts on Twitter that have a specific format and length restriction. The majority of them are written in the English language. As relatively few works have paid attention to sentiment analysis in the Russian and Kazakh languages, this article thoroughly analyzes news posts in the Kazakhstan media space. The amassed datasets include texts labeled according to three sentiment… More >

Farouq Aliyu^1,*, Tarek Sheltami¹, Ashraf Mahmoud¹, Louai Al-Awami¹, Ansar Yasar²

CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 1159-1181, 2021, DOI:10.32604/cmc.2021.016938

Abstract Fog computing (FC) is a networking paradigm where wireless devices known as fog nodes are placed at the edge of the network (close to the Internet of Things (IoT) devices). Fog nodes provide services in lieu of the cloud. Thus, improving the performance of the network and making it attractive to social media-based systems. Security issues are one of the most challenges encountered in FC. In this paper, we propose an anomaly-based Intrusion Detection and Prevention System (IDPS) against Man-in-the-Middle (MITM) attack in the fog layer. The system uses special nodes known as Intrusion Detection System (IDS) nodes to detect… More >

Shaheen Khatoon^1,*, Majed A. Alshamari¹, Amna Asif¹, Md Maruf Hasan¹, Sherif Abdou², Khaled Mostafa Elsayed³, Mohsen Rashwan⁴

CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3079-3100, 2021, DOI:10.32604/cmc.2021.017371

Abstract Social media platforms have proven to be effective for information gathering during emergency events caused by natural or human-made disasters. Emergency response authorities, law enforcement agencies, and the public can use this information to gain situational awareness and improve disaster response. In case of emergencies, rapid responses are needed to address victims’ requests for help. The research community has developed many social media platforms and used them effectively for emergency response and coordination in the past. However, most of the present deployments of platforms in crisis management are not automated, and their operational success largely depends on experts who analyze… More >

Youseef Alotaibi^1,*, Muhammad Noman Malik², Huma Hayat Khan³, Anab Batool², Saif ul Islam⁴, Abdulmajeed Alsufyani⁵, Saleh Alghamdi⁶

CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3323-3338, 2021, DOI:10.32604/cmc.2021.016727

Abstract Social media data are rapidly increasing and constitute a source of user opinions and tips on a wide range of products and services. The increasing availability of such big data on biased reviews and blogs creates challenges for customers and businesses in reviewing all content in their decision-making process. To overcome this challenge, extracting suggestions from opinionated text is a possible solution. In this study, the characteristics of suggestions are analyzed and a suggestion mining extraction process is presented for classifying suggestive sentences from online customers’ reviews. A classification using a word-embedding approach is used via the XGBoost classifier. The… More >

Nancy Awadallah Awad^1,*, Amena Mahmoud²

CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 1519-1530, 2021, DOI:10.32604/cmc.2021.016974

Abstract The rapid growth of the use of social media opens up new challenges and opportunities to analyze various aspects and patterns in communication. In-text mining, several techniques are available such as information clustering, extraction, summarization, classification. In this study, a text mining framework was presented which consists of 4 phases retrieving, processing, indexing, and mine association rule phase. It is applied by using the association rule mining technique to check the associated term with the Huawei P30 Pro phone. Customer reviews are extracted from many websites and Facebook groups, such as re-view.cnet.com, CNET. Facebook and amazon.com technology, where customers from… More >

Abdullah Alharbi^1,*, Wael Alosaimi¹, M. Irfan Uddin²

CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 303-317, 2021, DOI:10.32604/cmc.2021.016230

Abstract COVID-19 disease is spreading exponentially due to the rapid transmission of the virus between humans. Different countries have tried different solutions to control the spread of the disease, including lockdowns of countries or cities, quarantines, isolation, sanitization, and masks. Patients with symptoms of COVID-19 are tested using medical testing kits; these tests must be conducted by healthcare professionals. However, the testing process is expensive and time-consuming. There is no surveillance system that can be used as surveillance framework to identify regions of infected individuals and determine the rate of spread so that precautions can be taken. This paper introduces a… More >

Adnan A. Hnaif^1,*, Emran Kanan², Tarek Kanan¹

Intelligent Automation & Soft Computing, Vol.28, No.1, pp. 107-119, 2021, DOI:10.32604/iasc.2021.015939

Abstract In recent years, the use of social media has rapidly increased and developed significant influence on its users. In the study of the behavior, reactions, approval, and interactions of social media users, detecting the polarity (positive, negative, neutral) of news posts is of considerable importance. This proposed research aims to collect data from Arabic social media pages, with the posts comprising the main unit in the dataset, and to build a corpus of manually-processed data for training and testing. Applying Natural Language Processing to the data is crucial for the computer to understand and easily manipulate the data. Therefore, Stop-Word… More >

Huma¹, Muhammad Khalid Sohail², Nadeem Akhtar³, Dost Muhammad³, Humaira Afzal⁴, Muhammad Rafiq Mufti⁵, Shahid Hussain^6,*, Mansoor Ahmed¹

CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 3737-3748, 2021, DOI:10.32604/cmc.2021.014398

Abstract This study aims to identify the potential association of mental health and social media forum during the outbreak of COVID-19 pandemic. COVID-19 brings a lot of challenges to government globally. Among the different strategies the most extensively adopted ones were lockdown, social distancing, and isolation among others. Most people with no mental illness history have been found with high risk of distress and psychological discomfort due to anxiety of being infected with the virus. Panic among people due to COVID-19 spread faster than the disease itself. The misinformation and excessive usage of social media in this pandemic era have adversely… More >

Mazhar Javed Awan^1,2,*, Mohd Shafry Mohd Rahim², Haitham Nobanee^3,4,5, Ashna Munawar², Awais Yasin⁶, Azlan Mohd Zain ⁷

CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2569-2583, 2021, DOI:10.32604/cmc.2021.014253

Abstract Big data is the collection of large datasets from traditional and digital sources to identify trends and patterns. The quantity and variety of computer data are growing exponentially for many reasons. For example, retailers are building vast databases of customer sales activity. Organizations are working on logistics financial services, and public social media are sharing a vast quantity of sentiments related to sales price and products. Challenges of big data include volume and variety in both structured and unstructured data. In this paper, we implemented several machine learning models through Spark MLlib using PySpark, which is scalable, fast, easily integrated… More >

Samina Amin^1,*, M. Irfan Uddin¹, M. Ali Zeb¹, Ala Abdulsalam Alarood², Marwan Mahmoud³, Monagi H. Alkinani⁴

CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 1317-1332, 2021, DOI:10.32604/cmc.2021.014733

Abstract Social media platforms have lately emerged as a promising tool for predicting the outbreak of epidemics by analyzing information on them with the help of machine learning techniques. Many analytical and statistical models are available to infer a variety of user sentiments in posts on social media. The amount of data generated by social media platforms, such as Twitter, that can be used to track diseases is increasing rapidly. This paper proposes a method for the classification of tweets related to the outbreak of dengue using machine learning algorithms. An artificial neural network (ANN)-based method is developed using Global Vector… More >