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Full-Text Articles in Physical Sciences and Mathematics
Developing A Success Model Of A Social Student Relationship Management System, Wasef Mater, Monther Aldwairi, Nasim Matar, Waleed Al-Rahmi
Developing A Success Model Of A Social Student Relationship Management System, Wasef Mater, Monther Aldwairi, Nasim Matar, Waleed Al-Rahmi
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Social media's significance in higher education has increased due to its capacity to enhance participation, communication, teamwork, and information sharing. Important notifications, updates, and reminders can be promptly received by all members of the university community, assuring that information is shared with everyone. The objective of this study is to develop a model for a Customer Relationship Management (CRM) system in higher education that is based on social media and intends to increase student satisfaction, loyalty, and profitability. It blends the idea of trust with Delone Mclean success model. Partial Least Squares-Structural Equation Modeling (PLS-SEM) was used to evaluate the …
Of Stances, Themes, And Anomalies In Covid-19 Mask-Wearing Tweets, Jwen Fai Low, Benjamin C.M. Fung, Farkhund Iqbal, Ebrahim Bagheri
Of Stances, Themes, And Anomalies In Covid-19 Mask-Wearing Tweets, Jwen Fai Low, Benjamin C.M. Fung, Farkhund Iqbal, Ebrahim Bagheri
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COVID-19 is an opportunity to study public acceptance of a ‘‘new’’ healthcare intervention, universal masking, which unlike vaccination, is mostly alien to the Anglosphere public despite being practiced in ages past. Using a collection of over two million tweets, we studied the ways in which proponents and opponents of masking vied for influence as well as the themes driving the discourse. Pro-mask tweets encouraging others to mask up dominated Twitter early in the pandemic though its continued dominance has been eroded by anti-mask tweets criticizing others for their masking behavior. Engagement, represented by the counts of likes, retweets, and replies, …
Social Media Bot Detection With Deep Learning Methods: A Systematic Review, Kadhim Hayawi, Susmita Saha, Mohammad Mehedy Masud, Sujith Samuel Mathew, Mohammed Kaosar
Social Media Bot Detection With Deep Learning Methods: A Systematic Review, Kadhim Hayawi, Susmita Saha, Mohammad Mehedy Masud, Sujith Samuel Mathew, Mohammed Kaosar
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Social bots are automated social media accounts governed by software and controlled by humans at the backend. Some bots have good purposes, such as automatically posting information about news and even to provide help during emergencies. Nevertheless, bots have also been used for malicious purposes, such as for posting fake news or rumour spreading or manipulating political campaigns. There are existing mechanisms that allow for detection and removal of malicious bots automatically. However, the bot landscape changes as the bot creators use more sophisticated methods to avoid being detected. Therefore, new mechanisms for discerning between legitimate and bot accounts are …
Using Deep Learning To Detect Social Media ‘Trolls’, Áine Macdermott, Michal Motylinski, Farkhund Iqbal, Kellyann Stamp, Mohammed Hussain, Andrew Marrington
Using Deep Learning To Detect Social Media ‘Trolls’, Áine Macdermott, Michal Motylinski, Farkhund Iqbal, Kellyann Stamp, Mohammed Hussain, Andrew Marrington
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Detecting criminal activity online is not a new concept but how it can occur is changing. Technology and the influx of social media applications and platforms has a vital part to play in this changing landscape. As such, we observe an increasing problem with cyber abuse and ‘trolling’/toxicity amongst social media platforms sharing stories, posts, memes sharing content. In this paper we present our work into the application of deep learning techniques for the detection of ‘trolls’ and toxic content shared on social media platforms. We propose a machine learning solution for the detection of toxic images based on embedded …
Real-Time Tracking And Mining Of Users’ Actions Over Social Media, Ejub Kajan, Noura Faci, Zakaria Maamar, Mohamed Sellami, Emir Ugljanin, Hamamache Kheddouci, Dragan H. Stojanović, Djamal Benslimane
Real-Time Tracking And Mining Of Users’ Actions Over Social Media, Ejub Kajan, Noura Faci, Zakaria Maamar, Mohamed Sellami, Emir Ugljanin, Hamamache Kheddouci, Dragan H. Stojanović, Djamal Benslimane
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© 2020, ComSIS Consortium. All rights reserved. With the advent of Web 2.0 technologies and social media, companies are actively looking for ways to know and understand what users think and say about their products and services. Indeed, it has become the practice that users go online using social media like Facebook to raise concerns, make comments, and share recommendations. All these actions can be tracked in real-time and then mined using advanced techniques like data analytics and sentiment analysis. This paper discusses such tracking and mining through a system called Social Miner that allows companies to make decisions about …
Detecting Fake News In Social Media Networks, Monther Aldwairi, Ali Alwahedi
Detecting Fake News In Social Media Networks, Monther Aldwairi, Ali Alwahedi
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© 2018 The Authors. Published by Elsevier Ltd. Fake news and hoaxes have been there since before the advent of the Internet. The widely accepted definition of Internet fake news is: fictitious articles deliberately fabricated to deceive readers'. Social media and news outlets publish fake news to increase readership or as part of psychological warfare. Ingeneral, the goal is profiting through clickbaits. Clickbaits lure users and entice curiosity with flashy headlines or designs to click links to increase advertisements revenues. This exposition analyzes the prevalence of fake news in light of the advances in communication made possible by the emergence …
The Creation Of An Arabic Emotion Ontology Based On E-Motive, Anoud Bani-Hani, Munir Majdalweieh, Feras Obeidat
The Creation Of An Arabic Emotion Ontology Based On E-Motive, Anoud Bani-Hani, Munir Majdalweieh, Feras Obeidat
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© 2017 The Authors. Published by Elsevier B.V. There is an increased interest in social media monitoring to analyse massive, free form, short user-generated text from multiple social media sites such as Facebook, WhatsApp and Twitter. Companies are interested in sentiment analysis to understand customers' opinions about their products/services. Governments and law enforcement agencies are interested in identifying threats to safeguard their country's national security. They are actively seeking ways to monitor and analyse the public's responses to various services, activities and events, especially since social media has become a valuable real-time resource of information. This study builds on prior …