TL;DR: These sections of the Web break away from the page metaphor and are predicated on microcontent, which means that reading and searching this world is significantly different from searching the entire Web world.
TL;DR: In this article, a personalized trusted social network for a community of users, with little or no input from any given user, is presented, where one or more trusted sources are added to a user profile for the given user.
Abstract: Automated systems and methods are provided for establishing or maintaining a personalized trusted social network for a community of users, with little or no input from any given user. To establish the personalized trusted social network, one or more trusted sources are identified for a given user. The identified trusted sources are added to a user profile for the given user. Also, identified are any annotations, bookmarks, or the like that the identified trusted sources have associated with any shared content. These annotations provide access to microcontent items that the identified trusted sources have integrated with the shared content to thereby enhance or enrich its context. One or more profiles are constructed or updated to track the associations between the identified trusted sources and their annotations. The profile information can be applied to enhance and personalize search and browsing experiences for the given user.
TL;DR: In this paper, a system and a method for micro-content natural language processing are presented, comprising steps of receiving a microcontent message from a social networking server, tokenizing the micro-text message into one or more text tokens, detecting the language of the microtext message and selecting the property dictionary for part-of-speech tag, tagging the micro content message to identify related pronouns and nouns based on the selected dictionary, and extracting topics form the microcontent messages and assigning confidence values to the topics.
Abstract: A system and a method for microcontent natural language processing are presented. The method comprising steps of receiving a microcontent message from a social networking server, tokenizing the microcontent message into one or more text tokens, detecting the language of the microcontent message and selecting the property dictionary for part-of-speech tag, part-of-speech tagging the microcontent message to identify related pronouns and nouns based on the selected dictionary, and extracting topics form the microcontent messages and assigning confidence values to the topics.
TL;DR: Designing and delivering creative learning content using TikTok can benefit pedagogical methodologies based on nano-learning principles, thereby facilitating the creation of high-quality e-learning content.
Abstract: Social media platforms have influenced pedagogical practices, and given rise to new theoretical approaches that prioritize connected learning with the aim of improving the learning outcomes. Social media applications have raised the popularity of short videos which were originally created in accordance with micro-learning principles. The proliferation of social media and e-learning has led to the emergence of two overarching concepts: micro-learning and nano-learning. Nano-learning refers to the condensing of microcontent into small units that are controlled and delivered by learners to achieve a single learning objective. In this respect, the social media application TikTok can be a potential educational tool in future since it enables the delivery of small learning units in a short timespan (less than 60 seconds). Designing and delivering creative learning content using TikTok can benefit pedagogical methodologies based on nano-learning principles, thereby facilitating the creation of high-quality e-learning content.
TL;DR: This research suggests that the proposed here cloud-based app may serve as unique educational tool promoting the acquisition of subject-related knowledge and understanding as well as skills pertaining to data mining and, most importantly, news literacy.