Sex differences in intimate relationships

Social networks have turned out to be of fundamental importance both for our understanding human sociality and for the design of digital communication technology. However, social networks are themselves based on dyadic relationships and we have little understanding of the dynamics of close relationships and how these change over time. Evolutionary theory suggests that, even in monogamous mating systems, the pattern of investment in close relationships should vary across the lifespan when post-weaning investment plays an important role in maximising fitness. Mobile phone data sets provide us with a unique window into the structure of relationships and the way these change across the lifespan. We here use data from a large national mobile phone dataset to demonstrate striking sex differences in the pattern in the gender-bias of preferred relationships that reflect the way the reproductive investment strategies of the two sexes change across the lifespan: these differences mainly reflect women's shifting patterns of investment in reproduction and parental care. These results suggest that human social strategies may have more complex dynamics than we have tended to assume and a life-history perspective may be crucial for understanding them.Comment: 5 pages, 3 figures, contains electronic supplementary materia

SALSA: A Novel Dataset for Multimodal Group Behavior Analysis

Studying free-standing conversational groups (FCGs) in unstructured social settings (e.g., cocktail party ) is gratifying due to the wealth of information available at the group (mining social networks) and individual (recognizing native behavioral and personality traits) levels. However, analyzing social scenes involving FCGs is also highly challenging due to the difficulty in extracting behavioral cues such as target locations, their speaking activity and head/body pose due to crowdedness and presence of extreme occlusions. To this end, we propose SALSA, a novel dataset facilitating multimodal and Synergetic sociAL Scene Analysis, and make two main contributions to research on automated social interaction analysis: (1) SALSA records social interactions among 18 participants in a natural, indoor environment for over 60 minutes, under the poster presentation and cocktail party contexts presenting difficulties in the form of low-resolution images, lighting variations, numerous occlusions, reverberations and interfering sound sources; (2) To alleviate these problems we facilitate multimodal analysis by recording the social interplay using four static surveillance cameras and sociometric badges worn by each participant, comprising the microphone, accelerometer, bluetooth and infrared sensors. In addition to raw data, we also provide annotations concerning individuals' personality as well as their position, head, body orientation and F-formation information over the entire event duration. Through extensive experiments with state-of-the-art approaches, we show (a) the limitations of current methods and (b) how the recorded multiple cues synergetically aid automatic analysis of social interactions. SALSA is available at http://tev.fbk.eu/salsa.Comment: 14 pages, 11 figure

Human Motion Trajectory Prediction: A Survey

With growing numbers of intelligent autonomous systems in human environments, the ability of such systems to perceive, understand and anticipate human behavior becomes increasingly important. Specifically, predicting future positions of dynamic agents and planning considering such predictions are key tasks for self-driving vehicles, service robots and advanced surveillance systems. This paper provides a survey of human motion trajectory prediction. We review, analyze and structure a large selection of work from different communities and propose a taxonomy that categorizes existing methods based on the motion modeling approach and level of contextual information used. We provide an overview of the existing datasets and performance metrics. We discuss limitations of the state of the art and outline directions for further research.Comment: Submitted to the International Journal of Robotics Research (IJRR), 37 page

GoGlobal: How can contemporary design collaboration and e-commerce models grow the creative industries in developing countries?

Using previous case studies by the authors and a current live project, this paper considers whether the creative industries in a developing country (Ghana, Africa) can be nurtured through design collaboration and an e-commerce model to contribute significant economic growth through increasing international trade. The paper draws on practical experience of five annual projects, with a focus on GoGlobal Africa. Initiated in 2005, GoGlobal is a collaborative design research activity between the University of Technology Sydney, the Royal College of Art, the London School of Economics, RMIT Melbourne, and other partnering organisations. GoGlobal Africa was initiated in 2008 with 3 phases: creative studio with design students from the RCA UK and KNUST Ghana; an e-commerce process for supply, distribution and marketing; and a “hub” location to facilitate project delivery and dissemination. The context to GoGlobal is informed by the UNCTAD studies of global creative industries

GeoNotes: A Location-based Information System for Public Spaces

The basic idea behind location-based information systems is to connect information pieces to positions in outdoor or indoor space. Through position technologies such as Global Positioning System (GPS), GSM positioning, Wireless LAN positioning o

To Explore the Influence of AR-Filtered Selfies on Impression Management in Users' Intrapersonal Communication Under Computer-Mediated Communication (CMC)

Selfies are increasingly being shared on social media. On the basis of selfies, traditional beauty filters only finish tasks like whitening and face-lifting. However, with the introduction of augmented reality technology into selfie filters, more and more virtual impressions are presented, causing new influences on social media.This paper explores the influence of AR filters on the impressions management of selfie under Computer Mediad Communication (CMC) from the perspective of Goffman's (1959) dramaturgical theory. This study adopts a qualitative phenomenological research paradigm. Data were collected using document analysis, focus groups and in-depth interviews at two universities in Pingdingshan, China. Research has found that the media characteristics of AR filter selfies allow users to have a rich ability to choose and present their impressions, prompting users to project multiple impressions of themselves on social media. Let users be willing to communicate intrapersonally with AR selfies, thereby achieving self-improvement. This article expands the application scope of new media AR filters of dramaturgical theory in CMC. It also provides a basic understanding of the further communication influence of AR selfies on senders and receivers in CMC. This can provide relevant reference for the government to formulate media policies and manage social media platforms. It can also provide relevant research results as research by other relevant scholars