Catalogue Search | MBRL
Are you sure you want to remove the book from the shelf?
{{itemTitle}}
794
result(s) for
"Online social networks -- Computer programs"
Sort by:
Professional XMPP programming with JavaScript® and jQuery
Create real-time, highly interactive apps quickly with the powerful XMPP protocol XMPP is a robust protocol used for a wide range of applications, including instant messaging, multi-user chat, voice and video conferencing, collaborative spaces, real-time gaming, data synchronization, and search.
eBook
Analyzing social media networks with NodeXL : insights from a connected world
Analyzing Social Media Networks with NodeXL offers backgrounds in information studies, computer science, and sociology.This book is divided into three parts: analyzing social media, NodeXL tutorial, and social-media network analysis case studies.Part I provides background in the history and concepts of social media and social networks.
eBook
TweepFake: About detecting deepfake tweets
The recent advances in language modeling significantly improved the generative capabilities of deep neural models: in 2019 OpenAI released GPT-2, a pre-trained language model that can autonomously generate coherent, non-trivial and human-like text samples. Since then, ever more powerful text generative models have been developed. Adversaries can exploit these tremendous generative capabilities to enhance social bots that will have the ability to write plausible deepfake messages, hoping to contaminate public debate. To prevent this, it is crucial to develop deepfake social media messages detection systems. However, to the best of our knowledge no one has ever addressed the detection of machine-generated texts on social networks like Twitter or Facebook. With the aim of helping the research in this detection field, we collected the first dataset of real deepfake tweets, TweepFake . It is real in the sense that each deepfake tweet was actually posted on Twitter. We collected tweets from a total of 23 bots, imitating 17 human accounts. The bots are based on various generation techniques, i.e., Markov Chains, RNN, RNN+Markov, LSTM, GPT-2. We also randomly selected tweets from the humans imitated by the bots to have an overall balanced dataset of 25,572 tweets (half human and half bots generated). The dataset is publicly available on Kaggle. Lastly, we evaluated 13 deepfake text detection methods (based on various state-of-the-art approaches) to both demonstrate the challenges that Tweepfake poses and create a solid baseline of detection techniques. We hope that TweepFake can offer the opportunity to tackle the deepfake detection on social media messages as well.
Journal Article
Online social networks security and privacy: comprehensive review and analysis
With fast-growing technology, online social networks (OSNs) have exploded in popularity over the past few years. The pivotal reason behind this phenomenon happens to be the ability of OSNs to provide a platform for users to connect with their family, friends, and colleagues. The information shared in social network and media spreads very fast, almost instantaneously which makes it attractive for attackers to gain information. Secrecy and surety of OSNs need to be inquired from various positions. There are numerous security and privacy issues related to the user’s shared information especially when a user uploads personal content such as photos, videos, and audios. The attacker can maliciously use shared information for illegitimate purposes. The risks are even higher if children are targeted. To address these issues, this paper presents a thorough review of different security and privacy threats and existing solutions that can provide security to social network users. We have also discussed OSN attacks on various OSN web applications by citing some statistics reports. In addition to this, we have discussed numerous defensive approaches to OSN security. Finally, this survey discusses open issues, challenges, and relevant security guidelines to achieve trustworthiness in online social networks.
Journal Article
The App Generation
No one has failed to notice that the current generation of youth is deeply-some would say totally-involved with digital media. Professors Howard Gardner and Katie Davis name today's young people The App Generation, and in this spellbinding book they explore what it means to be \"app-dependent\" versus \"app-enabled\" and how life for this generation differs from life before the digital era.
Gardner and Davis are concerned with three vital areas of adolescent life: identity, intimacy, and imagination. Through innovative research, including interviews of young people, focus groups of those who work with them, and a unique comparison of youthful artistic productions before and after the digital revolution, the authors uncover the drawbacks of apps: they may foreclose a sense of identity, encourage superficial relations with others, and stunt creative imagination. On the other hand, the benefits of apps are equally striking: they can promote a strong sense of identity, allow deep relationships, and stimulate creativity. The challenge is to venture beyond the ways that apps are designed to be used, Gardner and Davis conclude, and they suggest how the power of apps can be a springboard to greater creativity and higher aspirations.
eBook
An Empirical Analysis of Seller Advertising Strategies in an Online Marketplace
Online marketplaces, such as Taobao, Amazon, and eBay, are increasingly adopting innovative business models such as paid advertising as an important revenue source. We study the effectiveness of two popular advertising tools, sponsored search and social media endorsement, in increasing online traffic and sales for online sellers at a retail e-commerce platform. We find that both sponsored search and social media endorsement can significantly increase traffic for sellers, with sponsored search being more effective than social media endorsement. However, only sponsored research has a positive and significant impact on sales. The two strategies also have differential effect on sellers with low and high reputations. Our findings are of great importance, as they provide additional insights into how these advertising tools can work more effectively in increasing traffic and sales for sellers with different reputation levels, thus providing important implications to guide the strategic choices for sellers as well as the platform.
Online marketplaces are increasingly adopting innovative business models such as paid advertising as a major revenue source. We study the effectiveness of two popular advertising tools, sponsored search and social media endorsement, in increasing traffic and sales for online sellers at a retail e-commerce platform. We find that, controlling for sellers’ self-selection behavior in choosing their strategies, both sponsored search and social media endorsement can significantly increase traffic for sellers, with sponsored search being more effective than social media endorsement. In contrast, only sponsored search has a positive and significant impact on sales. In examining the differential effects for sellers with low and high reputations, we find that sponsored search is more effective in increasing traffic for low-reputation sellers, but its effect on sales is larger for high-reputation sellers. Moreover, although social media endorsement increases traffic for sellers regardless of their reputation, it is effective in increasing sales for only high-reputation sellers. Our study provides important managerial implications to sellers as well as e-commerce platforms.
Journal Article
Detection of cross-site scripting (XSS) attacks using machine learning techniques: a review
With the rising demand for E-commerce, Social Networking websites, it has become essential to develop security protocols over the World Wide Web that can provide security and privacy to Internet users all over the globe. Several traditional encryption techniques and attack detection protocols can secure the data transmitted over public networks. However, hackers can effortlessly exploit them to acquire access to the users’ sensitive information such as user ID, session ID, cookies, passwords, bank account details, contact numbers, private PINs, database information, etc. Researchers have continuously innovated new techniques to build a secure and robust system that cannot be easily hacked and manipulated. Still, there is much scope for novelty to provide security against contemporary techniques used by intruders. The motivation of this survey is to observe the recent developments in Cross-Site Scripting attacks and techniques used by researchers to secure confidential information. Cross-Site Scripting (XSS) has been recognized as one of the top 10 online application security risks by the Open Web Application Security Project (OWASP) for decades. Therefore, dealing with this security flaw in web applications has become essential to avoid further personal and financial damage to Internet users and business organizations. There is a need for an extensive survey of recent XSS attack detection techniques that can provide the right direction to researchers and security professionals. We present a complete overview of recent machine learning and neural network-based XSS attack detection techniques in this paper, covering deep neural networks, decision trees, web-log-based detection models, and many more. This paper also highlights the research gaps that must be addressed while designing attack detection models. Further, challenges researchers face during the development of recent techniques are also discussed. Finally, future directions are provided to reflect on new concepts that can be used in forthcoming research works to improve XSS attack detection techniques.
Journal Article
Influence of MOOC learners discussion forum social interactions on online reviews of MOOC
Although some studies have explored massive open online courses (MOOCs) discussion forums and MOOC online reviews separately, studies of both aspects are insufficient. Based on the theory of self-determination, this paper proposes research hypotheses that MOOC learning progress has a direct impact on MOOC online reviews and an indirect influence on MOOC online reviews through social interactions in discussion forums, as well. Coursera the largest MOOC platform, is selected as the empirical research object, and data from learners who participated in the MOOC discussion forum and provided MOOC online reviews from August 2016 to December 2019 are obtained from the most popular course, “Machine Learning”. After processing, data from 4376 learners are obtained. Then, according to research hypotheses, multi regression models are constructed accordingly. The results show that the length of MOOC online review text is affected by the MOOC learning progress, the number of discussion forum posts, the number of follow, the online review sentiment and MOOC rating. This study highlights the main factors that affect MOOC online reviews. As a result, some suggestions are put forward for the construction of MOOC.
Journal Article
Online education via media platforms and applications as an innovative teaching method
Online teaching has globally become a part of the learning process and has been more well-established in developed countries. In developing countries, online teaching or e-Learning is not practiced or recognized officially by educational organizations and policymakers. On the other hand, it is well-known that computers and technology are the future; in such a case, the advancement of distance-learning or online learning is immensely remarkable. It has reduced teachers’ and students’ introversion concerning e-learning and technology and has provided a platform for learning new technologies and developing new skills. The recent COVID-19 lockdown impelled governments to start implementing E-learning in schools, which resulted in several challenges. This study attempts to analyze and interpret the challenges and potentials of implementing online learning by surveying through an online questionnaire using ‘Google Forms’ (N = 968) with responses from high school and primary school English teachers during the first week of March through the last week of April. The findings revealed that most teachers had negative perceptions of implementing e-learning for several reasons, including lack of essential facilities such as electricity, electronic devices, and the absence of required skills. The actual contributions of students and educators are also among the major obstacles. This research suggests introducing Information Communication Technology modules across media platforms and applications in the education departments, opening intensive courses for teachers, and developing educational facilities in the education departments and schools to overcome these limitations and challenges.
Journal Article