Pub Date : 2023-02-25DOI: 10.5121/csit.2023.130407
Kazuto Kakutani, Nobuhiro Ito, Kosuke Shima, Shintaro Oyama, T. Otsuka
In recent years, according to the sophistication of Medical Devices (MD), many portable MDs have been used and maintained with central management. However, the central management lends hospital staff the MDs only with managing by a ledger, therefore, missing or subletting may be caused. Furthermore, while the demand for the MDs is increasing due to the COVID-19, there is an issue that it is difficult to operate due to the shortage of clinical engineers against management duties of the MDs. In this study, we develop a power strip device which can measure electricity usage of plugged MD and its position and propose a visualization system for position and operation ratio of the MDs. We implemented 75 developed devices in three hospitals and confirmed that the system was effective to evaluate whether the number of the MDs owned by the hospital is appropriate.
{"title":"Development of a Monitoring System for the Management of Medical Devices","authors":"Kazuto Kakutani, Nobuhiro Ito, Kosuke Shima, Shintaro Oyama, T. Otsuka","doi":"10.5121/csit.2023.130407","DOIUrl":"https://doi.org/10.5121/csit.2023.130407","url":null,"abstract":"In recent years, according to the sophistication of Medical Devices (MD), many portable MDs have been used and maintained with central management. However, the central management lends hospital staff the MDs only with managing by a ledger, therefore, missing or subletting may be caused. Furthermore, while the demand for the MDs is increasing due to the COVID-19, there is an issue that it is difficult to operate due to the shortage of clinical engineers against management duties of the MDs. In this study, we develop a power strip device which can measure electricity usage of plugged MD and its position and propose a visualization system for position and operation ratio of the MDs. We implemented 75 developed devices in three hospitals and confirmed that the system was effective to evaluate whether the number of the MDs owned by the hospital is appropriate.","PeriodicalId":159989,"journal":{"name":"Computer Networks & Communications","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115237345","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-25DOI: 10.5121/csit.2023.130402
N. Akbari, A. Baniasadi
Deep Convolutional Neural Networks (CNNs) have achieved human-level performance in edge detection. However, there have not been enough studies on how to efficiently utilize the parameters of the neural network in edge detection applications. Therefore, the associated memory and energy costs remain high. In this paper, inspired by Depthwise Separable Convolutions and deformable convolutional networks (Deformable-ConvNet), we aim to address current inefficiencies in edge detection applications. To this end, we propose a new architecture, which we refer to as Lightweight Edge Detection Network (LEON ). The proposed approach is designed to integrate the advantages of the deformable unit and DepthWise Separable convolutions architecture to create a lightweight backbone employed for efficient feature extraction. As we show, we achieve state-of-the-art accuracy while significantly reducing the complexity by carefully choosing proper components for edge detection purposes. Our results on BSDS500 and NYUDv2 demonstrate that LEON outperforms the current lightweight edge detectors while requiring only 500k parameters. It is worth mentioning that we train the network from scratch without using pre- trained weights.
{"title":"LEON: Light Weight Edge Detection Network","authors":"N. Akbari, A. Baniasadi","doi":"10.5121/csit.2023.130402","DOIUrl":"https://doi.org/10.5121/csit.2023.130402","url":null,"abstract":"Deep Convolutional Neural Networks (CNNs) have achieved human-level performance in edge detection. However, there have not been enough studies on how to efficiently utilize the parameters of the neural network in edge detection applications. Therefore, the associated memory and energy costs remain high. In this paper, inspired by Depthwise Separable Convolutions and deformable convolutional networks (Deformable-ConvNet), we aim to address current inefficiencies in edge detection applications. To this end, we propose a new architecture, which we refer to as Lightweight Edge Detection Network (LEON ). The proposed approach is designed to integrate the advantages of the deformable unit and DepthWise Separable convolutions architecture to create a lightweight backbone employed for efficient feature extraction. As we show, we achieve state-of-the-art accuracy while significantly reducing the complexity by carefully choosing proper components for edge detection purposes. Our results on BSDS500 and NYUDv2 demonstrate that LEON outperforms the current lightweight edge detectors while requiring only 500k parameters. It is worth mentioning that we train the network from scratch without using pre- trained weights.","PeriodicalId":159989,"journal":{"name":"Computer Networks & Communications","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125993426","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-25DOI: 10.5121/csit.2023.130412
Yixin Liang, Marisabel Chang
Presentation is a skill that everyone has, and it is very commonly seen in companies, schools, conferences, etc [1]. And the purpose of a slide is to give the audience a better understanding of the topic and to add ideas that they forgot to mention [2]. It also adds visual support to the speaker's discussion. Usually the presenter held a slide remote or just used their computer to control the slide pace while presenting. However, the slide remote can often be unstable due to battery switching. Even those who do not have a slide remote are unable to ensure a smooth presentation because they need to constantly switch back and forth on the computer screen with the mouse, which not only makes the speaker more nervous but also likely to skip the slide. Slidecontroller uses existing AI technology, voice recognition, as a medium to allow users to enter the transition word used to switch slides [3]. For example, when the user enters "Now I am going to talk about'' when this word is spoken the Slidecontroller will receive the voice and match the speaker's turn to the next slide. The user can be creative with the keyword selection that best fits their presentation vibe. Or the user could use the Slidecontroller default option which controls the slide by simply saying “Next” to go to the next slide, “Previous” to go to the previous slide, and “Thank you” to stop the App to prevent from catching a similar keyword that accidentally switches the slide [4].
{"title":"A Desktop Application to Help Speakers Switch Slides by using AI and Voice Recognition","authors":"Yixin Liang, Marisabel Chang","doi":"10.5121/csit.2023.130412","DOIUrl":"https://doi.org/10.5121/csit.2023.130412","url":null,"abstract":"Presentation is a skill that everyone has, and it is very commonly seen in companies, schools, conferences, etc [1]. And the purpose of a slide is to give the audience a better understanding of the topic and to add ideas that they forgot to mention [2]. It also adds visual support to the speaker's discussion. Usually the presenter held a slide remote or just used their computer to control the slide pace while presenting. However, the slide remote can often be unstable due to battery switching. Even those who do not have a slide remote are unable to ensure a smooth presentation because they need to constantly switch back and forth on the computer screen with the mouse, which not only makes the speaker more nervous but also likely to skip the slide. Slidecontroller uses existing AI technology, voice recognition, as a medium to allow users to enter the transition word used to switch slides [3]. For example, when the user enters \"Now I am going to talk about'' when this word is spoken the Slidecontroller will receive the voice and match the speaker's turn to the next slide. The user can be creative with the keyword selection that best fits their presentation vibe. Or the user could use the Slidecontroller default option which controls the slide by simply saying “Next” to go to the next slide, “Previous” to go to the previous slide, and “Thank you” to stop the App to prevent from catching a similar keyword that accidentally switches the slide [4].","PeriodicalId":159989,"journal":{"name":"Computer Networks & Communications","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125104437","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-25DOI: 10.5121/csit.2023.130403
Catherine Hung
For online dancers, learning a dance move properly without the feedback of a live instructor can be challenging because it is difficult to determine whether a move is done correctly. The lack of proper guidance can result in doing a move incorrectly, causing injury. In this work – we explore the use of a hybrid Deep Learning/Machine Learning approach to classify dance moves as structurally correct or incorrect. Given a video clip of the dancer doing a move, such as the grand plie, the algorithm should detect the correctness of the movement. To capture the overall movement, we proposed various methods to process data, starting with deep learning techniques to convert video frames into landmarks. Next, we investigate several approaches to combining landmarks from multiple frames and training machine learning algorithms on the dataset. The distinction between correct and incorrect grand plies achieved accuracies of over 98%.
{"title":"A Machine Learning/Deep Learning Hybrid for Augmenting Teacher-LED Online Dance Education","authors":"Catherine Hung","doi":"10.5121/csit.2023.130403","DOIUrl":"https://doi.org/10.5121/csit.2023.130403","url":null,"abstract":"For online dancers, learning a dance move properly without the feedback of a live instructor can be challenging because it is difficult to determine whether a move is done correctly. The lack of proper guidance can result in doing a move incorrectly, causing injury. In this work – we explore the use of a hybrid Deep Learning/Machine Learning approach to classify dance moves as structurally correct or incorrect. Given a video clip of the dancer doing a move, such as the grand plie, the algorithm should detect the correctness of the movement. To capture the overall movement, we proposed various methods to process data, starting with deep learning techniques to convert video frames into landmarks. Next, we investigate several approaches to combining landmarks from multiple frames and training machine learning algorithms on the dataset. The distinction between correct and incorrect grand plies achieved accuracies of over 98%.","PeriodicalId":159989,"journal":{"name":"Computer Networks & Communications","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114081570","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-25DOI: 10.5121/csit.2023.130411
Shielanie Soriano Dacumos
Over the stretch of years, the Philippines has been facing numerous medical problems since the public outcry against a ‘dengue’ vaccine. As a result, parents refused their children from having an anti-measles vaccine which created a medical outbreak in the country. Product warnings are found to be in their optimal position in safeguarding the life of consumerpatients. This paper anatomizes the lexical features of medicine product warnings in the Philippines which are crucial in the response discourses. A range of linguistic frameworks were applied and significant findings were drawn. Lapses on the use of noun abstractness, synthetic personalization, field continuum, adjectives, and adverbs were identified. Such an investigation brought up the transparency of communicative features of medicine safety texts. In the end, linguistic components create a vital impact on the legal content adequacy of medicine product warnings, unfolding the vitalities of these messages in facilitating informed decisionmaking among consumer-patients.
{"title":"Lexical Features of Medicine Product Warnings in the Philippines","authors":"Shielanie Soriano Dacumos","doi":"10.5121/csit.2023.130411","DOIUrl":"https://doi.org/10.5121/csit.2023.130411","url":null,"abstract":"Over the stretch of years, the Philippines has been facing numerous medical problems since the public outcry against a ‘dengue’ vaccine. As a result, parents refused their children from having an anti-measles vaccine which created a medical outbreak in the country. Product warnings are found to be in their optimal position in safeguarding the life of consumerpatients. This paper anatomizes the lexical features of medicine product warnings in the Philippines which are crucial in the response discourses. A range of linguistic frameworks were applied and significant findings were drawn. Lapses on the use of noun abstractness, synthetic personalization, field continuum, adjectives, and adverbs were identified. Such an investigation brought up the transparency of communicative features of medicine safety texts. In the end, linguistic components create a vital impact on the legal content adequacy of medicine product warnings, unfolding the vitalities of these messages in facilitating informed decisionmaking among consumer-patients.","PeriodicalId":159989,"journal":{"name":"Computer Networks & Communications","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122509223","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-25DOI: 10.5121/csit.2023.130406
Noon Hussein
As of 2021, it has been reported that around 90% of data breaches occur on ac- count of phishing, while about 83% of organizations experienced phishing attacks [1]. Phishing can be defined as the cybercrime in which a target is contacted through e-mail, telephone or text message by someone impersonating a legitimate institution [2]. Through psychological manipulation, the threat actor attempts to deceive users into providing sensitive information, thereby causing financial and intellectual property losses, reputational damages, and operational activity disruption. In this light, this paper presents a comprehensive review of eyetracking in association with phishing cyberattacks. To determine their impact on phishing detection accuracy, this work reviews 20 empirical studies which measure eye-tracking metrics with respect to different Areas of Interest (AOIs). The described experiments aim to produce simple cognitive user reactions, examine concentration, perception and trust in the system; all in which determine the level of susceptibility to deception and manipulation. Results suggest that longer gaze durations on AOIs, characterized by higher attention control, are strongly correlated with detection accuracy. Eye-tracking behavior also shows that technical background, domain knowledge, experience, training, and risk perception con- tribute to mitigating these attacks. Meanwhile, Time to First Fixation (TTFF), entry time and entry sequence data yielded inconclusive results regarding the impact on susceptibility to phishing attacks. The results aid in designing user-friendly URLs, visual browsing aids, and embedded and automated authentication systems. Most importantly, these findings can be used to establish user awareness through the development of training programs. be used to establish user awareness through the development of training programs.
据报道，截至2021年，约90%的数据泄露发生在网络钓鱼中，而约83%的组织遭受过网络钓鱼攻击[1]。网络钓鱼可以定义为由冒充合法机构的人通过电子邮件、电话或短信联系目标的网络犯罪[2]。通过心理操纵，威胁参与者试图欺骗用户提供敏感信息，从而造成财务和知识产权损失、声誉损害和操作活动中断。鉴于此，本文对与网络钓鱼攻击相关的眼球追踪进行了全面的回顾。为了确定它们对网络钓鱼检测准确性的影响，本工作回顾了20项针对不同兴趣领域(aoi)测量眼球追踪指标的实证研究。所描述的实验旨在产生简单的认知用户反应，检查系统中的注意力，感知和信任;所有这些都决定了对欺骗和操纵的敏感程度。结果表明，注视aoi的时间越长，注意控制能力越强，与检测精度密切相关。眼动追踪行为还表明，技术背景、领域知识、经验、培训和风险感知有助于减轻这些攻击。与此同时，首次固定时间(Time to First Fixation, TTFF)、进入时间和进入顺序数据对网络钓鱼攻击易感性的影响尚无定论。其结果有助于设计用户友好的url、可视化浏览辅助工具以及嵌入式和自动化身份验证系统。最重要的是，这些发现可以用来通过开发培训计划来建立用户意识。通过开发培训计划来建立用户意识。
{"title":"Eye-tracking in Association with Phishing Cyber Attacks: a Comprehensive Literature Review","authors":"Noon Hussein","doi":"10.5121/csit.2023.130406","DOIUrl":"https://doi.org/10.5121/csit.2023.130406","url":null,"abstract":"As of 2021, it has been reported that around 90% of data breaches occur on ac- count of phishing, while about 83% of organizations experienced phishing attacks [1]. Phishing can be defined as the cybercrime in which a target is contacted through e-mail, telephone or text message by someone impersonating a legitimate institution [2]. Through psychological manipulation, the threat actor attempts to deceive users into providing sensitive information, thereby causing financial and intellectual property losses, reputational damages, and operational activity disruption. In this light, this paper presents a comprehensive review of eyetracking in association with phishing cyberattacks. To determine their impact on phishing detection accuracy, this work reviews 20 empirical studies which measure eye-tracking metrics with respect to different Areas of Interest (AOIs). The described experiments aim to produce simple cognitive user reactions, examine concentration, perception and trust in the system; all in which determine the level of susceptibility to deception and manipulation. Results suggest that longer gaze durations on AOIs, characterized by higher attention control, are strongly correlated with detection accuracy. Eye-tracking behavior also shows that technical background, domain knowledge, experience, training, and risk perception con- tribute to mitigating these attacks. Meanwhile, Time to First Fixation (TTFF), entry time and entry sequence data yielded inconclusive results regarding the impact on susceptibility to phishing attacks. The results aid in designing user-friendly URLs, visual browsing aids, and embedded and automated authentication systems. Most importantly, these findings can be used to establish user awareness through the development of training programs. be used to establish user awareness through the development of training programs.","PeriodicalId":159989,"journal":{"name":"Computer Networks & Communications","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121643709","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-25DOI: 10.5121/csit.2023.130410
Ruohan Zhang, Yaotian Zhang, Yu Sun
{"title":"A Smart Plantmoisture Level Determination System to Determine if the Plant Needs to be Watered or not by using Machine Learning","authors":"Ruohan Zhang, Yaotian Zhang, Yu Sun","doi":"10.5121/csit.2023.130410","DOIUrl":"https://doi.org/10.5121/csit.2023.130410","url":null,"abstract":"","PeriodicalId":159989,"journal":{"name":"Computer Networks & Communications","volume":"153 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120854612","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-25DOI: 10.5121/csit.2023.130401
Ziaul Hossain, G. Fairhurst
Popular Internet applications such as web browsing, web video download or variable-rate voice suffer from standard Transport Control Protocol (TCP) behaviour because their transmission rate and pattern are different from conventional bulk transfer applications. Previous works have analysed the interaction of these applications with the congestion control algorithms in TCP and proposed Congestion Window Validation (CWV) as a solution. However, this method was incomplete and has been shown to present drawbacks. This paper focuses on the ‘newCWV’ which was proposed to address these drawbacks. newCWV depicts a practical mechanism to estimate the available path capacity and suggests a more appropriate congestion control behaviour. These new modifications benefit variable-rate applications that are bursty in nature, with shorter transfer durations. In this paper, this algorithm was implemented in the Linux TCP/IP stack and tested by experiments, where results indicate that, with newCWV, the browsing can get 50% faster in an uncongested network.
{"title":"Measuring Performance of Web Protocol with Updated Transport Layer Techniques for Faster Web Browsing","authors":"Ziaul Hossain, G. Fairhurst","doi":"10.5121/csit.2023.130401","DOIUrl":"https://doi.org/10.5121/csit.2023.130401","url":null,"abstract":"Popular Internet applications such as web browsing, web video download or variable-rate voice suffer from standard Transport Control Protocol (TCP) behaviour because their transmission rate and pattern are different from conventional bulk transfer applications. Previous works have analysed the interaction of these applications with the congestion control algorithms in TCP and proposed Congestion Window Validation (CWV) as a solution. However, this method was incomplete and has been shown to present drawbacks. This paper focuses on the ‘newCWV’ which was proposed to address these drawbacks. newCWV depicts a practical mechanism to estimate the available path capacity and suggests a more appropriate congestion control behaviour. These new modifications benefit variable-rate applications that are bursty in nature, with shorter transfer durations. In this paper, this algorithm was implemented in the Linux TCP/IP stack and tested by experiments, where results indicate that, with newCWV, the browsing can get 50% faster in an uncongested network.","PeriodicalId":159989,"journal":{"name":"Computer Networks & Communications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125979578","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-25DOI: 10.5121/csit.2023.130413
S. Basit, Y. Goto
When an agent receives messages from other agents, it does belief revision. A belief revision includes, i) a trust reasoning process, i.e., it obtains new belief related to the messages, and deduces implicitly unknown beliefs from the obtained belief; ii) in the case of contradiction in the belief set, it resolves the contradiction. So, trust reasoning, and belief revision must be included in the decision-making process of an intelligent agent in multi-agent systems. Although a belief revision mechanism with trust reasoning is demanded to construct multi-agent systems, there is no such belief revision mechanism. We, therefore, present a belief revision mechanism with trust reasoning based on extended reciprocal logic for multi-agent systems.
{"title":"A Belief Revision Mechanism with Trust Reasoning based on Extended Reciprocal Logic for Multi-Agent Systems","authors":"S. Basit, Y. Goto","doi":"10.5121/csit.2023.130413","DOIUrl":"https://doi.org/10.5121/csit.2023.130413","url":null,"abstract":"When an agent receives messages from other agents, it does belief revision. A belief revision includes, i) a trust reasoning process, i.e., it obtains new belief related to the messages, and deduces implicitly unknown beliefs from the obtained belief; ii) in the case of contradiction in the belief set, it resolves the contradiction. So, trust reasoning, and belief revision must be included in the decision-making process of an intelligent agent in multi-agent systems. Although a belief revision mechanism with trust reasoning is demanded to construct multi-agent systems, there is no such belief revision mechanism. We, therefore, present a belief revision mechanism with trust reasoning based on extended reciprocal logic for multi-agent systems.","PeriodicalId":159989,"journal":{"name":"Computer Networks & Communications","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130810773","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-25DOI: 10.5121/csit.2023.130404
Suha Khalil Assayed, K. Shaalan, M. Alkhatib, Safwan Maghaydah
The various types of social media were increased rapidly, as people’s need to share knowledge between others. In fact, there are various types of social media apps and platforms such as Facebook, Twitter, Reddit, Instagram, and others. Twitter remains one of the most popular social application that people use for sharing their emotional states. However, this has increased particularly during the COVID-19 pandemic. In this paper, we proposed a chatbot for evaluating the sentiment analysis by using machine learning algorithms. The authors used a dataset of tweets from Kaggle’s website, and that includes 41157 tweets that are related to the COVID-19. These tweets were classified and labelled to four categories: Extremely positive, positive, neutral, negative, and extremely negative. In this study, we applied Machine Learning algorithms, Support Vector Machines (SVM), and the Naïve Bayes (NB) algorithms and accordingly, we compared the accuracy between them. In addition to that, the classifiers were evaluated and compared after changing the test split ratio. The result shows that the accuracy performance of SVM algorithm is better than Naïve Bayes algorithm, even though Naïve Bayes perform poorly with low accuracy, but it trained the data faster comparing to SVM.
{"title":"Machine Learning Chatbot for Sentiment Analysis of Covid-19 Tweets","authors":"Suha Khalil Assayed, K. Shaalan, M. Alkhatib, Safwan Maghaydah","doi":"10.5121/csit.2023.130404","DOIUrl":"https://doi.org/10.5121/csit.2023.130404","url":null,"abstract":"The various types of social media were increased rapidly, as people’s need to share knowledge between others. In fact, there are various types of social media apps and platforms such as Facebook, Twitter, Reddit, Instagram, and others. Twitter remains one of the most popular social application that people use for sharing their emotional states. However, this has increased particularly during the COVID-19 pandemic. In this paper, we proposed a chatbot for evaluating the sentiment analysis by using machine learning algorithms. The authors used a dataset of tweets from Kaggle’s website, and that includes 41157 tweets that are related to the COVID-19. These tweets were classified and labelled to four categories: Extremely positive, positive, neutral, negative, and extremely negative. In this study, we applied Machine Learning algorithms, Support Vector Machines (SVM), and the Naïve Bayes (NB) algorithms and accordingly, we compared the accuracy between them. In addition to that, the classifiers were evaluated and compared after changing the test split ratio. The result shows that the accuracy performance of SVM algorithm is better than Naïve Bayes algorithm, even though Naïve Bayes perform poorly with low accuracy, but it trained the data faster comparing to SVM.","PeriodicalId":159989,"journal":{"name":"Computer Networks & Communications","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129834353","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：