Polarization in social movements on Twitter

Online social networks have become a parallel universe of socialization from which interactive dynamics are generated until recently unknown. From this framework of online communication, different social movements have reached a greater boom and spread. On Twitter these social movements have as a characteristic feature a hashtag (#) that allows cross-cutting the conversation. Although it has become an instrument that makes it possible to agglutinate the conversation in a massive way, we are also emerging voices that warn of the growing manipulation around these forms of socialization. Social workers must pay attention and investigate these means of digital activism in order to understand and avoid these possible manipulations. In this communication we analyze in a longitudinal way different social movements on Twitter. To this end, social movements that have emerged during the last year about phenomena related to the empowerment of women (#metoo, #yositecreo, etc ...), cooperation against natural disasters (#mallorca) and social demands (# pensions). To identify leaderships, detect communities and measure social distances, social network analysis has been used as well as certain algorithms. For the analysis of the conversations, language analysis techniques have been used to optimize the combination of the most common words, giving rise to conversation patterns around certain force ideas. The results achieved show a high level of emotivity in the way of interacting and a significant pattern of polarization in conversations about these movements that is the seed of conflicts and radicalization. The key lies in the way we congregate and converse in networks around those with whom we share our perspectives and opinions about the world. This tendency towards homophily provokes a biased and monolithic vision of reality. In order to counteract these conflicts we must raise the level of self-awareness on the level of homophilia in the way we congregate and converse on online social networks and intervene to increase tolerance for diversity.Online social networks have become a parallel universe of socialization from which interactive dynamics are generated until recently unknown. From this framework of online communication, different social movements have reached a greater boom and spread. On Twitter these social movements have as a characteristic feature a hashtag (#) that allows cross-cutting the conversation. Although it has become an instrument that makes it possible to agglutinate the conversation in a massive way, we are also emerging voices that warn of the growing manipulation around these forms of socialization. Social workers must pay attention and investigate these means of digital activism in order to understand and avoid these possible manipulations. In this communication we analyze in a longitudinal way different social movements on Twitter. To this end, social movements that have emerged during the last year about phenomena related to the empowerment of women (#metoo, #yositecreo, etc ...), cooperation against natural disasters (#mallorca) and social demands (# pensions). To identify leaderships, detect communities and measure social distances, social network analysis has been used as well as certain algorithms. For the analysis of the conversations, language analysis techniques have been used to optimize the combination of the most common words, giving rise to conversation patterns around certain force ideas.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Using pattern languages to mediate theory–praxis conversations in design for networked learning

Educational design for networked learning is becoming more complex but also more inclusive, with teachers and learners playing more active roles in the design of tasks and of the learning environment. This paper connects emerging research on the use of design patterns and pattern languages with a conception of educational design as a conversation between theory and praxis. We illustrate the argument by drawing on recent empirical research and literature reviews from the field of networked learning

Semantic Variation in Online Communities of Practice

We introduce a framework for quantifying semantic variation of common words in Communities of Practice and in sets of topic-related communities. We show that while some meaning shifts are shared across related communities, others are community-specific, and therefore independent from the discussed topic. We propose such findings as evidence in favour of sociolinguistic theories of socially-driven semantic variation. Results are evaluated using an independent language modelling task. Furthermore, we investigate extralinguistic features and show that factors such as prominence and dissemination of words are related to semantic variation.Comment: 13 pages, Proceedings of the 12th International Conference on Computational Semantics (IWCS 2017

Kaleidoscope JEIRP on Learning Patterns for the Design and Deployment of Mathematical Games: Final Report

Project deliverable (D40.05.01-F)Over the last few years have witnessed a growing recognition of the educational potential of computer games. However, it is generally agreed that the process of designing and deploying TEL resources generally and games for mathematical learning specifically is a difficult task. The Kaleidoscope project, "Learning patterns for the design and deployment of mathematical games", aims to investigate this problem. We work from the premise that designing and deploying games for mathematical learning requires the assimilation and integration of deep knowledge from diverse domains of expertise including mathematics, games development, software engineering, learning and teaching. We promote the use of a design patterns approach to address this problem. This deliverable reports on the project by presenting both a connected account of the prior deliverables and also a detailed description of the methodology involved in producing those deliverables. In terms of conducting the future work which this report envisages, the setting out of our methodology is seen by us as very significant. The central deliverable includes reference to a large set of learning patterns for use by educators, researchers, practitioners, designers and software developers when designing and deploying TEL-based mathematical games. Our pattern language is suggested as an enabling tool for good practice, by facilitating pattern-specific communication and knowledge sharing between participants. We provide a set of trails as a "way-in" to using the learning pattern language. We report in this methodology how the project has enabled the synergistic collaboration of what started out as two distinct strands: design and deployment, even to the extent that it is now difficult to identify those strands within the processes and deliverables of the project. The tools and outcomes from the project can be found at: http://lp.noe-kaleidoscope.org

Mediators of Inequity: Online Literate Activity in Two Eighth Grade English Language Arts Classes

This comparative case study, framed by Cultural Historical Activity Theory and sociocultural understandings of literacy, investigated students’ online literate activity in two eighth grade English Language Arts classes taught by the same teacher - one with a scripted literacy curriculum and the other without. During a year-long research project, we used ethnographic methods to explore the nature of middle school students’ literate activity in each of these classes, with particular attention to the mediators evident as students engaged in online literate activity. Specifically, this article addresses the following research question: What mediators were evident within and across each of the classes and how did these mediators influence students’ online literate activity? In addressing this question, we illustrate how particular configurations of mediators – even those operating within the context of the same school and same teacher – significantly influenced the nature of students’ online literate activity and the literate identities available to students. This study reinforces the importance of attending to the influence of offline mediators in school settings. Without such attention, students’ formal education is likely to be transferred online rather than transformed online

Automatic Detection of Online Jihadist Hate Speech

We have developed a system that automatically detects online jihadist hate speech with over 80% accuracy, by using techniques from Natural Language Processing and Machine Learning. The system is trained on a corpus of 45,000 subversive Twitter messages collected from October 2014 to December 2016. We present a qualitative and quantitative analysis of the jihadist rhetoric in the corpus, examine the network of Twitter users, outline the technical procedure used to train the system, and discuss examples of use.Comment: 31 page

Evaluative Language and Its Solidarity-Building Role on TED.com: An Appraisal and Corpus Analysis

Language is a key resource in the formation of online communities, which are in turn central to an understanding of contemporary social relations. This study looks at TED.com, an educational video-hosting platform with few in-built community-building functionalities, to explore the potential for users to affiliate through their language choices. Grounded in Systemic Functional Linguistics, the study uses the Appraisal framework, extended using corpus linguistic methods, in order to analyse users’ reactions to TED videos. The study shows that online participants use evaluative language to align with certain ideas and, based on these affinities, form affiliations characterized by sociability and solidarity. These affiliations raise important questions about the conception of ‘community’ in twenty-first century society