Fostering Social Interaction Through Sound Feedback: Sentire

Sentire is a body–machine interface that sonifies motor behaviour in real time and a participatory, interactive performance in which two people use their physical movements to collaboratively create sound while constantly being influenced by the results. Based on our informal observation that basal social behaviours emerge during Sentire performances, the present article investigates our principal hypothesis that Sentire can foster basic mechanisms underlying non-verbal social interaction. We illustrate how coordination serves as a crucial basic mechanism for social interaction, and consider how it is addressed by various therapeutic approaches, including therapeutic use of real-time auditory feedback. Then we argue that the implementation of Sentire may be fruitful in healthcare contexts and in promoting general well-being. We describe how the Sentire system has been developed further within the scope of the research project ‘Social interaction through sound feedback–Sentire’ that combines human–computer interaction, sound design and real-world research, against the background of the relationship between sound, sociality and therapy. The question concerning how interaction is facilitated through Sentire is addressed through the first results of behavioural analysis using structured observation, which allows for a quasi-quantitative sequential analysis of interactive behaviour.Peer Reviewe

Detecting and Tracking the Spread of Astroturf Memes in Microblog Streams

Online social media are complementing and in some cases replacing person-to-person social interaction and redefining the diffusion of information. In particular, microblogs have become crucial grounds on which public relations, marketing, and political battles are fought. We introduce an extensible framework that will enable the real-time analysis of meme diffusion in social media by mining, visualizing, mapping, classifying, and modeling massive streams of public microblogging events. We describe a Web service that leverages this framework to track political memes in Twitter and help detect astroturfing, smear campaigns, and other misinformation in the context of U.S. political elections. We present some cases of abusive behaviors uncovered by our service. Finally, we discuss promising preliminary results on the detection of suspicious memes via supervised learning based on features extracted from the topology of the diffusion networks, sentiment analysis, and crowdsourced annotations

Understanding Virtuality: Contributions from Goffman’s Frame Analysis

Virtual interactions are normally assumed to be separate and distinct from the “real world,” yet they are also situated within material reality. In this paper I propose that a situated approach to understanding virtuality can be developed through drawing from Goffman’s Frame Analysis (1974/1986). I explain how Goffman’s terminology and concepts afford a way of integrating the study of virtual interaction with the study of social interaction more generally. His frame analysis approach offers constructs useful for distinguishing virtual worlds from each other and from real worlds in a way that is consonant with perspectives on human-computer interaction. His language can help to account for the phenomenon of immersion in virtual worlds; and it is well suited for understanding co-present and mediated social interaction at the same time. I conclude by discussing some limitations of this approach and suggesting directions for further research

Statistical Proof and Theories of Discrimination

We live in a tightly knit world. Our emotions, desires, perceptions and decisions are interlinked in our interactions with others. We are constantly influencing our surroundings and being influenced by others. In this thesis, we unfold some aspects of social and economical interactions by studying empirical datasets. We project these interactions into a network representation to gain insights on how socio-economic systems form and function and how they change over time. Specifically, this thesis is centered on four main questions: How do the means of communication shape our social network structures? How can we uncover the underlying network of interests from massive observational data? How does a crisis spread in a real financial network? How do the dynamics of interaction influence spreading processes in networks? We use a variety of methods from physics, psychology, sociology, and economics as well as computational, mathematical and statistical analysis to address these questions

Two Screen Viewing and Social Relationships. Exploring the invisible backchannel of TV viewing

Use of social networks to create a real-time backchannel of\ud communication among viewers of television programs has been documented, and has been termed “two-screen viewing,” with one screen devoted to the program being watched, and a second screen (usually a laptop, tablet, or cell/mobile\ud phone) devoted to maintaining the backchannel. Prior research has examined twoscreen viewing through content analysis of social media posts. However, little has been done to explore the way in which two screen viewing qualitatively changes the viewing experience, or to understand how this behavior contributes to the construction or maintenance of social relationships. Couch (1992) noted that social interaction require a shared focus, a social objective, and congruent functional identities. The first screen program provides the shared focus. Using online interviews, this small pilot project seeks to discover whether social objectives and congruent functional identities are established through two-screen viewing. That is, the study explores how one might go about determining whether this communication actually contributes to social relationships or serves some other, asocial purpose. The present study is a small pilot project only. Preliminary\ud data suggest that there are two types of two-screen viewing defined by different degrees of visible and invisible online practice