Influence of augmented humans in online interactions during voting events

The advent of the digital era provided a fertile ground for the development of virtual societies, complex systems influencing real-world dynamics. Understanding online human behavior and its relevance beyond the digital boundaries is still an open challenge. Here we show that online social interactions during a massive voting event can be used to build an accurate map of real-world political parties and electoral ranks. We provide evidence that information flow and collective attention are often driven by a special class of highly influential users, that we name "augmented humans", who exploit thousands of automated agents, also known as bots, for enhancing their online influence. We show that augmented humans generate deep information cascades, to the same extent of news media and other broadcasters, while they uniformly infiltrate across the full range of identified groups. Digital augmentation represents the cyber-physical counterpart of the human desire to acquire power within social systems.Comment: 11 page

Expanding the theoretical base for the dynamics of willingness to communicate

The dynamics underlying willingness to communicate in a second or third language (L2 for short), operating in real time, are affected by a number of intra- and inter-personal processes. L2 communication is a remarkably fluid process, especially considering the wide range of skill levels observed among L2 learners and speakers. Learners often find themselves in a position that requires the use of uncertain L2 skills, be it inside or outside the classroom context. Beyond issues of competencies, which are themselves complex, using an L2 also evokes cultural, political, social, identity, motivational, emotional, pedagogical, and other issues that learners must navigate on-the-fly. The focus of this article will be on the remarkably rapid integration of factors, such as the ones just named whenever a language learner chooses to be a language speaker, that is, when the moment for authentic communication arrives. Communicative events are especially important in understanding the psychology of the L2 learner. Our research group has developed the idiodynamic method to allow examination of an individual’s experience of events on a timescale of a few minutes. Results are describing complex interactions and rapid changes in the psychological conditions that accompany both approaching and avoiding L2 communication. The research takes a new approach to familiar concepts such as motivation, language competence, learning strategies, and so on. By examining willingness to communicate as a dynamic process, new types of research questions and answers are emerging, generating new theory, research methods, and pedagogical approaches applicable both within language classrooms and beyond

Detecting Real-World Influence Through Twitter

In this paper, we investigate the issue of detecting the real-life influence of people based on their Twitter account. We propose an overview of common Twitter features used to characterize such accounts and their activity, and show that these are inefficient in this context. In particular, retweets and followers numbers, and Klout score are not relevant to our analysis. We thus propose several Machine Learning approaches based on Natural Language Processing and Social Network Analysis to label Twitter users as Influencers or not. We also rank them according to a predicted influence level. Our proposals are evaluated over the CLEF RepLab 2014 dataset, and outmatch state-of-the-art ranking methods.Comment: 2nd European Network Intelligence Conference (ENIC), Sep 2015, Karlskrona, Swede