Abstract-The field of usability, user experience (UX) design and human-computer interaction (HCI) arose in the realm of desktop computers and applicat ions. The current experience in co mputing has radically evolved into ubiquitous computing over the preceding years. Interactions these days take place on different devices: mobile phones, e-readers and smart TVs, amid numerous smart devices. The use of one service across mult iple devices is, at present, common with different form factors. Academic researchers are still try ing to figure out the best design techniques for new devices and experiences. The Internet of Things (IoT) is growing, with an ever wider range of daily objects acquiring connectivity, sensing ability and increased computing power. Designing for IoT raises a lot of challenges; the obvious difference being the much wider variety of device form factors. IoT is still a technically driven field, thus the usability of many of IoT products is, in some way, of the level anticipated of mature consumer products. This study focuses on proposing a usability evaluation criterion for the generic IoT architecture and essential technological components.

The exponential growth of social media has spurred an increase in the propagation of hate nowadays. Recent evidence shows that hate speech on social media is detrimental to the mental and physical health of individuals. Thus, there is an emerging need for automated hate speech detection. Automated hate speech detection rests on the intersection between Natural Language Processing (NLP) techniques and machine learning models. An introduction of NLP and its utilities, as well as commonly employed features and classification methods in hate speech detection, are discussed. Hate speech detection in non-English languages is needed to tackle this emergent issue in countries where multiple languages are used. Hence, an overview of the current literature on hate speech detection in non-English languages are covered too. Challenges in the field of hate speech detection are explored and the importance of standardized methodologies for building corpora and data sets are emphasized.

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