scholarly journals Effectiveness of Supervised Classification Models for Hate Speech on Twitter

2020 ◽  
Author(s):  
Kunal Srivastava ◽  
Ryan Tabrizi ◽  
Ayaan Rahim ◽  
Lauryn Nakamitsu
Keyword(s):  
Supervised Classification ◽  
Hate Speech ◽  
The Internet ◽  
Classification Models ◽  
Personal Attack ◽  
Political Beliefs ◽  
The Many ◽  
Primary Medium ◽  
Offensive Speech

<div> <div> <div> <p>Abstract </p> <p>The ceaseless connectivity imposed by the internet has made many vulnerable to offensive comments, be it their physical appearance, political beliefs, or religion. Some define hate speech as any kind of personal attack on one’s identity or beliefs. Of the many sites that grant the ability to spread such offensive speech, Twitter has arguably become the primary medium for individuals and groups to spread these hurtful comments. Such comments typically fail to be detected by Twitter’s anti-hate system and can linger online for hours before finally being taken down. Through sentiment analysis, this algorithm is able to distinguish hate speech effectively through the classification of sentiment. </p> </div> </div> </div>

Effectiveness of Supervised Classification Models for Hate Speech on Twitter

2020 ◽  
Author(s):  
Kunal Srivastava ◽  
Ryan Tabrizi ◽  
Ayaan Rahim ◽  
Lauryn Nakamitsu
Keyword(s):  
Supervised Classification ◽  
Hate Speech ◽  
The Internet ◽  
Classification Models ◽  
Personal Attack ◽  
Political Beliefs ◽  
The Many ◽  
Primary Medium ◽  
Offensive Speech

<div> <div> <div> <p>Abstract </p> <p>The ceaseless connectivity imposed by the internet has made many vulnerable to offensive comments, be it their physical appearance, political beliefs, or religion. Some define hate speech as any kind of personal attack on one’s identity or beliefs. Of the many sites that grant the ability to spread such offensive speech, Twitter has arguably become the primary medium for individuals and groups to spread these hurtful comments. Such comments typically fail to be detected by Twitter’s anti-hate system and can linger online for hours before finally being taken down. Through sentiment analysis, this algorithm is able to distinguish hate speech effectively through the classification of sentiment. </p> </div> </div> </div>

scholarly journals Dehumanizacja w komentarzach internetowych w polskich portalach informacyjnych. Identyfikacja i klasyfikacja zjawiska na przykładzie odbioru Fransa Timmermansa

2021 ◽  
Vol 9 (3) ◽  
pp. 451-474
Author(s):  
Arkadiusz Domagała
Keyword(s):  
Literature Review ◽  
European Commission ◽  
Hate Speech ◽  
Vice President ◽  
The Internet ◽  
Right Wing ◽  
The Right ◽  
The Relationship

Dehumanization in the Internet Comments on Polish News Portals. Identification and Classification of the Phenomenon, on the Example of the Reception of Franz Timmermans The paper addresses the issue of the main types of dehumanization in the Polish right-wing portals (wPolityce, DoRzeczy, Republika) and the conceptualization of hypotheses concerning the relationship between framing and the content of comments on the Vice-President of the European Commission, Frans Timmermans. The premise of the paper is that an article and its comments form a specific entity and in tandem constitute its essence (global sense) together. In the literature review, some types of dehumanization were distinguished: animalization, biologization, objectification, subhumanization, demonization. An insectization was added as an extremely hateful form of de-humanization. Then the role of political hate speech and selected forms of dehumanization in the portals was determined by specially prepared indicators. Comments in the right-wing identity portals like wPolityce and Republika are specific with the noticeable role of insectization and demonization. Subsequently, the dehumanization comments in right-wing portals were compared with the comments on TVPInfo and Gazeta.pl. The latters, in comparison to right-wing portals, turned out to be similar when it comes to dehumanization as such and political hate speech, but contained a limited number of dehumanization forms. Frames based on conflict were consistently used in all the portals. However, the right-wing portals were distinguished by a much greater role of moral frames, which, combined with expressive linguistic forms, constituted strong frames.

ASPECTS IN BUILDING A COMPANY WEB-SITE AND ITS ROLE FOR THE DEVELOPMENT OF BUSINESS

2018 ◽  
pp. 117-124
Author(s):  
Petar Halachev ◽  
Victoria Radeva ◽  
Albena Nikiforova ◽  
Miglena Veneva
Keyword(s):  
Life Cycle ◽  
Web Site ◽  
The Internet ◽  
A Company ◽  
The Web ◽  
Design Construction ◽  
Made In ◽  
Site Types

This report is dedicated to the role of the web site as an important tool for presenting business on the Internet. Classification of site types has been made in terms of their application in the business and the types of structures in their construction. The Models of the Life Cycle for designing business websites are analyzed and are outlined their strengths and weaknesses. The stages in the design, construction, commissioning, and maintenance of a business website are distinguished and the activities and requirements of each stage are specified.

Das Internet der Tiere: Natur 4.0 und die conditio humana

2016 ◽  
Vol 7 (2) ◽  
pp. 111-124
Author(s):  
Alexander Pschera
Keyword(s):  
Industry 4.0 ◽  
Industrie 4.0 ◽  
Human Condition ◽  
Digital Culture ◽  
The Internet ◽  
Conditio Humana ◽  
The Many ◽  
The Human Condition

"Neben der Industrie hat die Digitalisierung auch die Natur ergriffen. Die Tatsache, dass Tausende von Tieren mit GPS-Sendern aus- gerüstet und überwacht werden, erlaubt, analog zur Industrie 4.0 auch von einer Natur 4.0 zu sprechen. Dieses Internet der Tiere verändert den Begriff, den der Mensch von der Natur hat. Er transformiert die Wahrnehmung vor allem der Natur als etwas fundamental An- deren. Neben den vielen kulturellen Problematisierungen, die das Internet der Tiere mit sich bringt, lassen sich aber auch die Umrisse einer neuen, ganz und gar nicht esoterischen planetarisch-post-digitalen Kultur aufzeigen, die die conditio humana verändert. In addition to industry, digitalization has also taken hold of nature. The fact that thousands of animals are provided and monitored with GPS transmitters allows to speak of nature 4.0 by way of analogy to industry 4.0. This internet of animals changes our idea of nature. Most of all, it transforms the perception of nature as something fundamentally other. Beside the many cultural problems that the internet of animals implies, it can also outline a new, not at all esoteric planetary post-digital culture that is about to change the human condition. "

Future Directions

2020 ◽  
pp. 476-479
Author(s):  
Marc N. Potenza ◽  
Kyle A. Faust ◽  
David Faust
Keyword(s):  
Technology Development ◽  
Digital Technologies ◽  
World Health ◽  
International Classification Of Disease ◽  
Levels Of Use ◽  
Pornography Use ◽  
Negative Impacts ◽  
Mental Health Treatments ◽  
The Many

As digital technology development continues to expand, both its positive and negative applications have also grown. As such, it is essential to continue gathering data on the many types of digital technologies, their overall effects, and their impact on public health. The World Health Organization’s inclusion of Gaming Disorder in the eleventh edition of the International Classification of Disease (ICD-11) indicates that some of the problematic effects of gaming are similar to those of substance-use disorders and gambling. Certain behaviors easily engaged in via the internet may also lead to compulsive levels of use in certain users, such as shopping or pornography use. In contrast, digital technologies can also lead to improvements in and wider accessibility to mental health treatments. Furthermore, various types of digital technologies can also lead to benefits such as increased productivity or social functioning. By more effectively understanding the impacts of all types of digital technologies, we can aim to maximize their benefits while minimizing or preventing their negative impacts.

scholarly journals A Machine Learning Approach to Study Glycosidase Activities from Bifidobacterium

2021 ◽  
Vol 9 (5) ◽  
pp. 1034
Author(s):  
Carlos Sabater ◽  
Lorena Ruiz ◽  
Abelardo Margolles
Keyword(s):  
Machine Learning ◽  
Supervised Classification ◽  
Machine Learning Algorithms ◽  
Learning Approach ◽  
Human Milk Oligosaccharides ◽  
Future Studies ◽  
High Fiber ◽  
Machine Learning Approach ◽  
Prebiotic Oligosaccharides

This study aimed to recover metagenome-assembled genomes (MAGs) from human fecal samples to characterize the glycosidase profiles of Bifidobacterium species exposed to different prebiotic oligosaccharides (galacto-oligosaccharides, fructo-oligosaccharides and human milk oligosaccharides, HMOs) as well as high-fiber diets. A total of 1806 MAGs were recovered from 487 infant and adult metagenomes. Unsupervised and supervised classification of glycosidases codified in MAGs using machine-learning algorithms allowed establishing characteristic hydrolytic profiles for B. adolescentis, B. bifidum, B. breve, B. longum and B. pseudocatenulatum, yielding classification rates above 90%. Glycosidase families GH5 44, GH32, and GH110 were characteristic of B. bifidum. The presence or absence of GH1, GH2, GH5 and GH20 was characteristic of B. adolescentis, B. breve and B. pseudocatenulatum, while families GH1 and GH30 were relevant in MAGs from B. longum. These characteristic profiles allowed discriminating bifidobacteria regardless of prebiotic exposure. Correlation analysis of glycosidase activities suggests strong associations between glycosidase families comprising HMOs-degrading enzymes, which are often found in MAGs from the same species. Mathematical models here proposed may contribute to a better understanding of the carbohydrate metabolism of some common bifidobacteria species and could be extrapolated to other microorganisms of interest in future studies.

scholarly journals Sparse Autoencoder-based Multi-head Deep Neural Networks for Machinery Fault Diagnostics with Detection of Novelties

2021 ◽  
Vol 34 (1) ◽  
Author(s):  
Zhe Yang ◽  
Dejan Gjorgjevikj ◽  
Jianyu Long ◽  
Yanyang Zi ◽  
Shaohui Zhang ◽  
...  
Keyword(s):  
Fault Diagnosis ◽  
Supervised Classification ◽  
Deep Neural Networks ◽  
Activation Function ◽  
Reconstruction Error ◽  
Fine Tuning ◽  
Fault Diagnostics ◽  
Sparse Autoencoder

AbstractSupervised fault diagnosis typically assumes that all the types of machinery failures are known. However, in practice unknown types of defect, i.e., novelties, may occur, whose detection is a challenging task. In this paper, a novel fault diagnostic method is developed for both diagnostics and detection of novelties. To this end, a sparse autoencoder-based multi-head Deep Neural Network (DNN) is presented to jointly learn a shared encoding representation for both unsupervised reconstruction and supervised classification of the monitoring data. The detection of novelties is based on the reconstruction error. Moreover, the computational burden is reduced by directly training the multi-head DNN with rectified linear unit activation function, instead of performing the pre-training and fine-tuning phases required for classical DNNs. The addressed method is applied to a benchmark bearing case study and to experimental data acquired from a delta 3D printer. The results show that its performance is satisfactory both in detection of novelties and fault diagnosis, outperforming other state-of-the-art methods. This research proposes a novel fault diagnostics method which can not only diagnose the known type of defect, but also detect unknown types of defects.

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