The popularity of online social networks has created massive social communication among their users and this leads to a huge amount of user-generated communication data. In recent years, ...Cyberbullying has grown into a major problem with the growth of online communication and social media. Cyberbullying has been recognized recently as a serious national health issue among online social network users and developing an efficient detection model holds tremendous practical significance. In this paper, we have proposed set of unique features derived from Twitter; network, activity, user, and tweet content, based on these feature, we developed a supervised machine learning solution for detecting cyberbullying in the Twitter. An evaluation demonstrates that our developed detection model based on our proposed features, achieved results with an area under the receiver-operating characteristic curve of 0.943 and an f-measure of 0.936. These results indicate that the proposed model based on these features provides a feasible solution to detecting Cyberbullying in online communication environments. Finally, we compare result obtained using our proposed features with the result obtained from two baseline features. The comparison outcomes show the significance of the proposed features.
•We propose a set of unique features based on tweets information to detect cyberbullying.•Machine learning model based on the proposed features is developed.•The developed model is effective in detecting cyberbullying in the Twitter network.
What happens when the human brain, which evolved over eons,
collides with twenty-first-century technology? Machines can now
push psychological buttons, stimulating and sometimes exploiting
the ways ...people make friends, gossip with neighbors, and grow
intimate with lovers. Sex robots present the humanoid face of this
technological revolution-yet although it is easy to gawk at their
uncanniness, more familiar technologies based in artificial
intelligence and virtual reality are insinuating themselves into
human interactions. Digital lovers, virtual friends, and
algorithmic matchmakers help us manage our feelings in a world of
cognitive overload. Will these machines, fueled by masses of user
data and powered by algorithms that learn all the time, transform
the quality of human life? Artificial Intimacy offers an
innovative perspective on the possibilities of the present and near
future. The evolutionary biologist Rob Brooks explores the latest
research on intimacy and desire to consider the interaction of new
technologies and fundamental human behaviors. He details how
existing artificial intelligences can already learn and exploit
human social needs-and are getting better at what they do. Brooks
combines an understanding of core human traits from evolutionary
biology with analysis of how cultural, economic, and technological
contexts shape the ways people express them. Beyond the technology,
he asks what the implications of artificial intimacy will be for
how we understand ourselves.
YouTube hosts one billion visitors monthly and sees more than 400 hours of video uploaded every minute. In “Thanks for Watching,” Patricia Lange offers an anthropological perspective on this heavily ...mediated social environment, demonstrating how core concepts from anthropology—participant-observation, reciprocity, and community—apply to sociality on YouTube and how to reconceptualize and update these concepts for video-sharing cultures.
Drawing on 152 interviews with YouTube participants at gatherings throughout the United States, content analyses of more than 300 videos, observations of interactions on and off the site, and participant-observation (in which a researcher becomes part of the community she examines), Lange provides new insight into patterns of digital migration, YouTube’s influence on interactions even off-site, and how the loss of control over image makes users feel post-human.
How craigslist champions openness, democracy, and other vanishing principles of the early web Begun by Craig Newmark as an e-mail to some friends about cool events happening around San Francisco, ...craigslist is now the leading classifieds service on the planet. It is also a throwback to the early internet. The website has barely seen an upgrade since it launched in 1996. There are no banner ads. The company doesn't profit off your data. An Internet for the People explores how people use craigslist to buy and sell, find work, and find love—and reveals why craigslist is becoming a lonely outpost in an increasingly corporatized web.Drawing on interviews with craigslist insiders and ordinary users, Jessa Lingel looks at the site's history and values, showing how it has mostly stayed the same while the web around it has become more commercial and far less open. She examines craigslist's legal history, describing the company's courtroom battles over issues of freedom of expression and data privacy, and explains the importance of locality in the social relationships fostered by the site. More than an online garage sale, job board, or dating site, craigslist holds vital lessons for the rest of the web. It is a website that values user privacy over profits, ease of use over slick design, and an ethos of the early web that might just hold the key to a more open, transparent, and democratic internet.
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. Also included here is social network analysis, which flows from measuring, to mapping, and modeling collections of connections. The next part focuses on the detailed operation of the free and open-source NodeXL extension of Microsoft Excel, which is used in all exercises throughout this book. In the final part, each chapter presents one form of social media, such as e-mail, Twitter, Facebook, Flickr, and Youtube. In addition, there are descriptions of each system, the nature of networks when people interact, and types of analysis for identifying people, documents, groups, and events. * Walks you through NodeXL, while explaining the theory and development behind each step, providing takeaways that can apply to any SNA * Demonstrates how visual analytics research can be applied to SNA tools for the mass market * Includes case studies from researchers who use NodeXL on popular networks like email, Facebook, Twitter, and wikis * Download companion materials and resources at https://nodexl.codeplex.com/documentation
Sentiment analysis has become a key tool for several social media applications, including, analysis of user’s opinions about products and services, support for politics during campaigns and even ...identification of market trending. Multiple existing sentiment analysis methods explore different techniques, usually relying on lexical resources or learning approaches. Despite the significant interest in this theme and amount of research efforts in the field, almost all existing methods are designed to work with only English content. Most current strategies in other languages consist of adapting existing lexical resources, without presenting proper validations and basic baseline comparisons. In this work, we take a different step into this field. We focus on evaluating existing efforts proposed to do language specific sentiment analysis with a simple yet effective baseline approach. To do it, we evaluated sixteen methods for sentence-level sentiment analysis proposed for English, and compared them with three language-specific methods. Based on fourteen human labeled language-specific datasets, we provide an extensive quantitative analysis of existing multilingual approaches. Our results suggest that simply translating the input text in a specific language to English and then using one of the existing best methods developed for English can be better than the existing language-specific approach evaluated. We also rank methods according to their prediction performance and identify those that acquired the best results using machine translation across different languages. As a final contribution to the research community, we release our codes, datasets, and the iFeel 3.0 system, a Web framework and tool for multilingual sentence-level sentiment analysis11iFeel resources: https://sites.google.com/view/ifeel-resources/home.. We hope our system sets up a new baseline for future sentence-level methods developed in a wide set of languages.
Rumor spreading in OSNs has been posing a significant threat to maintain the normal social order. In recent years, extensive efforts have been directed towards studying the rumor dynamics based on ...epidemic models, assuming that only the rumor cascades exist in the network for a specific event. In this paper, a novel rumor spreading model called ILRDS is proposed to describe the rumor dynamics in OSNs under emergencies. Different from previous studies, the model considers that when an ignorant is exposed to a rumor or counter-rumor, he or she will change into a latent with one of three different attitudes toward the rumor. Furthermore, the influence of debunking behavior and varying total population on the rumor dynamics are also investigated in this paper. Then, the stability of ILRDS model is analyzed by using the Lyapunov function-based method and Poincarè–Bendixson property. Finally, simulations are carried out to describe the influence of different parameters on the rumor spreading process, and the corresponding management strategies for restraining the rumor spreading under the emergencies are also discussed in this paper.
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