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16+ results
Field: Spam and Phishing Detection

Sentiment analysis on large scale Amazon product reviews

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Tanjim Ul Haque, Nudrat Nawal Saber, Faisal Muhammad Shah

Year: 2018Citations: 259

The world we see nowadays is becoming more digitalized. In this digitalized world e-commerce is taking the ascendancy by making products available within the reach of customers where the customer doesn't have to go out of their house. As now a day's people are relying on online products so the impor...

Physical SciencesComputer ScienceArtificial Intelligence
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A Comprehensive Review on Fake News Detection With Deep Learning

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M. F. Mridha, Ashfia Jannat Keya, Md. Abdul Hamid, Muhammad Mostafa Monowar et al.

Journal: IEEE AccessYear: 2021Citations: 252

A protuberant issue of the present time is that, organizations from different domains are struggling to obtain effective solutions for detecting online-based fake news. It is quite thought-provoking to distinguish fake information on the internet as it is often written to deceive users. Compared wit...

Social SciencesSociology and Political ScienceMisinformation and Its ImpactsOpen Access
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A benchmark study of machine learning models for online fake news detection

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Junaed Younus Khan, Md. Tawkat Islam Khondaker, Sadia Afroz, Gias Uddin et al.

Journal: Machine Learning with ApplicationsYear: 2021Citations: 233

The proliferation of fake news and its propagation on social media has become a major concern due to its ability to create devastating impacts. Different machine learning approaches have been suggested to detect fake news. However, most of those focused on a specific type of news (such as political)...

Social SciencesSociology and Political ScienceMisinformation and Its ImpactsOpen Access
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Sentiment Analysis on Twitter Data using KNN and SVM

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Mohammad Rezwanul, Ahmad Ali, A. S.A. Rahman

Journal: International Journal of Advanced Computer Science and ApplicationsYear: 2017Citations: 184

Millions of users share opinions on various topics using micro-blogging every day. Twitter is a very popular micro-blogging site where users are allowed a limit of 140 characters; this kind of restriction makes the users be concise as well as expressive at the same time. For that reason, it becomes ...

Physical SciencesComputer ScienceArtificial IntelligenceOpen Access
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Phishing Attacks Detection using Machine Learning Approach

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Mohammad Nazmul Alam, Dhiman Sarma, Farzana Firoz Lima, Ishita Saha et al.

Journal: 2020 Third International Conference on Smart Systems and Inventive Technology (ICSSIT)Year: 2020Citations: 151

Evolving digital transformation has exacerbated cybersecurity threats globally. Digitization expands the doors wider to cybercriminals. Initially cyberthreats approach in the form of phishing to steal the confidential user credentials. Usually, Hackers will influence the users through phishing in or...

Physical SciencesComputer ScienceInformation Systems
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Detecting Fake News using Machine Learning and Deep Learning Algorithms

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Abdullah All Tanvir, Ehesas Mia Mahir, Saima Akhter, Mohammad Rezwanul Huq

Year: 2019Citations: 145

Social media interaction especially the news spreading around the network is a great source of information nowadays. From one's perspective, its negligible exertion, straightforward access, and quick dispersing of information that lead people to look out and eat up news from internet-based life. Twi...

Social SciencesSociology and Political ScienceMisinformation and Its Impacts
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Detection of Distributed Denial of Service (DDoS) Attacks in IOT Based Monitoring System of Banking Sector Using Machine Learning Models

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Umar Islam, Ali Muhammad, Rafiq Mansoor, Md Shamim Hossain et al.

Journal: SustainabilityYear: 2022Citations: 144

Cyberattacks can trigger power outages, military equipment problems, and breaches of confidential information, i.e., medical records could be stolen if they get into the wrong hands. Due to the great monetary worth of the data it holds, the banking industry is particularly at risk. As the number of ...

Physical SciencesComputer ScienceComputer Networks and CommunicationsOpen Access
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COVID-19 Public Sentiment Insights and Machine Learning for Tweets Classification

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Jim Samuel, Md. Mokhlesur Rahman, G. G. Md. Nawaz Ali, Ek Esawi et al.

Year: 2020Citations: 130

Along with the Coronavirus pandemic, another crisis has manifested itself in the form of mass fear and panic phenomena, fueled by incomplete and often inaccurate information. There is therefore a tremendous need to address and better understand COVID-19's informational crisis and gauge public sentim...

Social SciencesSociology and Political ScienceMisinformation and Its ImpactsOpen Access
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Sentiment analysis on twitter tweets about COVID-19 vaccines usi ng NLP and supervised KNN classification algorithm

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F. M. Javed Mehedi Shamrat, Sovon Chakraborty, Mubashir Imran, Jannatun Naeem Muna et al.

Journal: Indonesian Journal of Electrical Engineering and Computer ScienceYear: 2021Citations: 123

The pandemic has taken the world by storm. Almost the entire world went into lockdown to save the people from the deadly COVID-19. Scientists around the around have come up with several vaccines for the virus. Amongthem, Pfizer, Moderna, and AstraZeneca have become quite famous. General people howev...

Physical SciencesComputer ScienceArtificial IntelligenceOpen Access
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An algorithm and method for sentiment analysis using the text and emoticon

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Mohammad Aman Ullah, Syeda Maliha Marium, Shamim Ara Begum, Nibadita Saha Dipa

Journal: ICT ExpressYear: 2020Citations: 123

People nowadays use emoticons in their text increasingly in order to express their feelings or recapitulate their words. Earlier machine learning techniques only involve the classification of text, emoticons or images solely where emoticons with text have always been neglected, thus ignored lots of ...

Physical SciencesComputer ScienceArtificial IntelligenceOpen Access
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Ransomware Classification and Detection With Machine Learning Algorithms

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Mohammad Masum, Md Jobair Hossain Faruk, Hossain Shahriar, Kai Qian et al.

Journal: 2022 IEEE 12th Annual Computing and Communication Workshop and Conference (CCWC)Year: 2022Citations: 112

Malicious attacks, malware, and ransomware families pose critical security issues to cybersecurity, and it may cause catastrophic damages to computer systems, data centers, web, and mobile applications across various industries and businesses. Traditional anti-ransomware systems struggle to fight ag...

Physical SciencesComputer ScienceSignal ProcessingOpen Access
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A deep learning model for Twitter spam detection

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Zulfikar Alom, Barbara Carminati, Elena Ferrari

Journal: Online Social Networks and MediaYear: 2020Citations: 110

Social networking platforms have become a popular way for Internet surfers to meet and interact. Twitter is one of the most popular social networking platforms where users can read the news, share ideas, discuss social issues, as well as stay in touch with friends and families. Due to its huge popul...

Physical SciencesComputer ScienceInformation SystemsOpen Access
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A Deep Learning Approach to Detect Abusive Bengali Text

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Estiak Ahmed Emon, Shihab Rahman, Joti Banarjee, Amit Kumar Das et al.

Year: 2019Citations: 110

Day by day, Social media sites, online news portals and blogs commenting sections are getting saturated with abusive contents in Bangladesh. Detecting different types of abusive contents in online will not only improve these websites discussion sections but will also ensure user's safety. In this pa...

Physical SciencesComputer ScienceArtificial Intelligence
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Multi-class sentiment classification on Bengali social media comments using machine learning

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Rezaul Haque, Naimul Islam, Mayisha Tasneem, Amit Das

Journal: International Journal of Cognitive Computing in EngineeringYear: 2023Citations: 107

Multi-class Sentiment Analysis (SA) is an important field of computational linguistics that extracts multiple opinions expressed in a text using NLP and text-mining techniques. Existing research on multi-class SA in the Bengali language is directed towards ternary classification with unsatisfactory ...

Physical SciencesComputer ScienceArtificial IntelligenceOpen Access
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Modeling Hybrid Feature-Based Phishing Websites Detection Using Machine Learning Techniques

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Sumitra Das Guptta, Khandaker Tayef Shahriar, Hamed Alqahtani, Dheyaaldin Alsalman et al.

Journal: Annals of Data ScienceYear: 2022Citations: 107

In this paper, we mainly present a machine learning based approach to detect real-time phishing websites by taking into account URL and hyperlink based hybrid features to achieve high accuracy without relying on any third-party systems. In phishing, the attackers typically try to deceive internet us...

Physical SciencesComputer ScienceInformation SystemsOpen Access
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