Daily Stress Recognition from Mobile Phone Data, Weather Conditions and Individual Traits

Research has proven that stress reduces quality of life and causes many diseases. For this reason, several researchers devised stress detection systems based on physiological parameters. However, these systems require that obtrusive sensors are continuously carried by the user. In our paper, we propose an alternative approach providing evidence that daily stress can be reliably recognized based on behavioral metrics, derived from the user's mobile phone activity and from additional indicators, such as the weather conditions (data pertaining to transitory properties of the environment) and the personality traits (data concerning permanent dispositions of individuals). Our multifactorial statistical model, which is person-independent, obtains the accuracy score of 72.28% for a 2-class daily stress recognition problem. The model is efficient to implement for most of multimedia applications due to highly reduced low-dimensional feature space (32d). Moreover, we identify and discuss the indicators which have strong predictive power.Comment: ACM Multimedia 2014, November 3-7, 2014, Orlando, Florida, US

A Data-Driven Approach for Modeling Agents

Agents are commonly created on a set of simple rules driven by theories, hypotheses, and assumptions. Such modeling premise has limited use of real-world data and is challenged when modeling real-world systems due to the lack of empirical grounding. Simultaneously, the last decade has witnessed the production and availability of large-scale data from various sensors that carry behavioral signals. These data sources have the potential to change the way we create agent-based models; from simple rules to driven by data. Despite this opportunity, the literature has neglected to offer a modeling approach to generate granular agent behaviors from data, creating a gap in the literature. This dissertation proposes a novel data-driven approach for modeling agents to bridge the research gap. The approach is composed of four detailed steps including data preparation, attribute model creation, behavior model creation, and integration. The connection between and within each step is established using data flow diagrams. The practicality of the approach is demonstrated with a human mobility model that uses millions of location footprints collected from social media. In this model, the generation of movement behavior is tested with five machine learning/statistical modeling techniques covering a large number of model/data configurations. Results show that Random Forest-based learning is the most effective for the mobility use case. Furthermore, agent attribute values are obtained/generated with machine learning and translational assignment techniques. The proposed approach is evaluated in two ways. First, the use case model is compared to another model which is developed using a state-of-the-art data-driven approach. The model’s prediction performance is comparable to the state-of-the-art model. The plausibility of behaviors and model structure in the use case model is found to be closer to real-world than the state-of-the-art model. This outcome indicates that the proposed approach produces realistic results. Second, a standard mobility dataset is used for driving the mobility model in place of social media data. Despite its small size, the data and model resembled the results gathered from the primary use case indicating the possibility of using different datasets with the proposed approach

Sustainable consumption: towards action and impact. : International scientific conference November 6th-8th 2011, Hamburg - European Green Capital 2011, Germany: abstract volume

This volume contains the abstracts of all oral and poster presentations of the international scientific conference „Sustainable Consumption – Towards Action and Impact“ held in Hamburg (Germany) on November 6th-8th 2011. This unique conference aims to promote a comprehensive academic discourse on issues concerning sustainable consumption and brings together scholars from a wide range of academic disciplines. In modern societies, private consumption is a multifaceted and ambivalent phenomenon: it is a ubiquitous social practice and an economic driving force, yet at the same time, its consequences are in conflict with important social and environmental sustainability goals. Finding paths towards “sustainable consumption” has therefore become a major political issue. In order to properly understand the challenge of “sustainable consumption”, identify unsustainable patterns of consumption and bring forward the necessary innovations, a collaborative effort of researchers from different disciplines is needed

Being cosmopolitan: the consumption practices and behaviors of consumers betwixt and between marketplaces

Contemporary global nomadism is an emerging phenomenon enabled by the far-reaching forces of globalization, whereby people voluntarily chose to embrace lifestyles of continuous mobility be- tween different countries and cultures. This research examines how do nomadic cosmopolitan consumers navigate through diverse constellations of sociocultural environments, marketplace offerings, possessions, experiences and brands while transitioning from one location to another. Following the theoretical paradigms of practice theory, this study advances the notion that cosmo- politan nomadism is a complex social practice – consisting of material artifacts, skills, routines, teleoaffective structures, and cultural understandings – which attracts and “recruits” individuals, and which becomes a foundational building block of their social life. Based on insight from a series of phenomenological interviews with nomadic cosmopolitans, it is suggested that consumption emerges through and for the sake of migrants’ participation as practitioners in the nomadic cos- mopolitan practice. Within this operational context, meanings, doings and material artifacts are orchestrated through three primary dispersed practices of anchoring, immersion and divestment. Consumption varies within each of those practices as they influence the kinds of brands, products and possessions consumers orient themselves towards, or detach from, throughout the temporal phases that segment the length of time one spends in a certain location – namely, phases of arri- val, settling in and departure. The perspective offered by this study illuminates a new theoretical angle through which we can begin to better understand the trajectory of possessions, brands, experiences and beliefs in condi- tions of continuous transnational mobility. It shows that nomadic cosmopolitanism is dynamic and individually differentiated – hence, it is the fact of one’s unique way of engagement in the practice that explains individuated processes of consumption. This research suggests that percep- tions of value and utility, as well as symbolic meaning of objects and activities, pivot around com- plex cognitive structures and subject positions, and evolve continuously as one changes as a practi- tioner, not only in the grander scheme of his/her life, but also within the temporal frame of a single residency

Population-scale dietary interests during the COVID-19 pandemic.

The SARS-CoV-2 virus has altered people's lives around the world. Here we document population-wide shifts in dietary interests in 18 countries in 2020, as revealed through time series of Google search volumes. We find that during the first wave of the COVID-19 pandemic there was an overall surge in food interest, larger and longer-lasting than the surge during typical end-of-year holidays in Western countries. The shock of decreased mobility manifested as a drastic increase in interest in consuming food at home and a corresponding decrease in consuming food outside of home. The largest (up to threefold) increases occurred for calorie-dense carbohydrate-based foods such as pastries, bakery products, bread, and pies. The observed shifts in dietary interests have the potential to globally affect food consumption and health outcomes. These findings can inform governmental and organizational decisions regarding measures to mitigate the effects of the COVID-19 pandemic on diet and nutrition

Quantifying Quality of Life

Describes technological methods and tools for objective and quantitative assessment of QoL Appraises technology-enabled methods for incorporating QoL measurements in medicine Highlights the success factors for adoption and scaling of technology-enabled methods This open access book presents the rise of technology-enabled methods and tools for objective, quantitative assessment of Quality of Life (QoL), while following the WHOQOL model. It is an in-depth resource describing and examining state-of-the-art, minimally obtrusive, ubiquitous technologies. Highlighting the required factors for adoption and scaling of technology-enabled methods and tools for QoL assessment, it also describes how these technologies can be leveraged for behavior change, disease prevention, health management and long-term QoL enhancement in populations at large. Quantifying Quality of Life: Incorporating Daily Life into Medicine fills a gap in the field of QoL by providing assessment methods, techniques and tools. These assessments differ from the current methods that are now mostly infrequent, subjective, qualitative, memory-based, context-poor and sparse. Therefore, it is an ideal resource for physicians, physicians in training, software and hardware developers, computer scientists, data scientists, behavioural scientists, entrepreneurs, healthcare leaders and administrators who are seeking an up-to-date resource on this subject

Reconciling structure and agency in strategy -as-practice research: Towards a strong- structuration theory approach

An overwhelming focus of research on the micro agency of strategic actors has led to the literature being characterized as demonstrating a micro-myopia, resulting in a micro-isolationism. This means we know little about how the micro interrelates with the macro in strategy work. We address this problem in our conceptual article which adopts a structurationist stance to explicate how strategy-as-practice (SaP) research could be enhanced and extended by paying equal attention to both agency and structure. Specifically, we advance strong structuration theory (SST), a promising development from Giddens’ seminal work on structuration theory, to show how strategic activity can be understood as an ongoing process of structuration unfolding over time. We argue for the use of both types of methodological bracketing (context and conduct analysis), advocating systematic attention to the interplay between macro-societal and micro-local levels of analysis. Our discussion concludes with guidance for researchers inviting them to undertake empirical fieldwork that overcomes SaP’s current micro-myopia, creating a more balanced corpus of work