Unacquainted People Research Articles

Language Choice and the Multilingual Soundscape: Overhearing as a Resource for Recipient-Design in Impromptu First-Time Encounters

ABSTRACT When previously unacquainted people spontaneously strike up a conversation in multilingual public space, a fundamental practical problem with which they may be faced is language choice. Using video recordings of naturally-occurring first-time encounters collected in a variety of public settings, this article shows that one way of calibrating initial language choice in emergent encounters is by taking advantage of overhearables in the immediate environment. Analysis demonstrates how incidentally co-present individuals who are within earshot of one another aurally monitor co-present others and accountably exploit their sensory access to a previously-in-progress interaction for then implementing a recipient-oriented, linguistically fitted action when moving into focused interaction, thereby using overhearing as an occasioned resource for recipient-design. The analysis contributes to the study of openings between strangers in public space and our understanding of the relation between embodied participation and everyday multilingualism-in-interaction. Data are in (lingua franca) English, French, Italian, Standard German, and Swiss German.

Implementing the Fast Friends Procedure to Build Camaraderie in a Remote Synchronous Teaching Setting

Introduction Improving students’ experiences in courses has always been important; one important method for facilitating discussions is an effective icebreaker activity. Statement of the Problem The move to remote learning during the COVID-19 pandemic presented new challenges for fostering connections among students. Given the constraints in remote learning, teachers need effective and feasible ways to improve student experiences. Literature Review We reviewed traditional icebreaker activities and highlighted the potential for implementing the Fast Friends procedure in a remotely delivered synchronous class. This procedure involves a discussion guided by a series of increasingly intimate questions meant to enhance connection between unacquainted people. Teaching Implications Undergraduate and graduate students reported having a positive experience and building connections from the procedure, including enhanced classroom motivation. We share materials so interested readers and teachers can easily implement this. Conclusion The Fast Friends procedure is a promising icebreaker activity to include at the start of the semester that can help students have a positive experience and build connection with classmates.

The role of furry friends in facilitating social interaction during the COVID-19 pandemic

The COVID-19 pandemic disrupted social interactions unprecedently. Schools closed, people worked from home, and many were confined to interacting via social media and video chats. Studies have shown the psychological benefits of pet ownership. However, little research has been done on how and if the presence of a pet affects social interactions with strangers, especially during a socially isolated global pandemic. We set out to answer the question: will a dog walk change social interactions with strangers? We hypothesized that walking with a dog can change human-to-human interaction and help start conversations with unacquainted people. We conducted this experiment during six dog walks on randomly selected trails. We studied how walking with and without a dog affects interaction with other walkers. There were 245 observations in the study group (walking with a dog) and 208 in the control group (walking without a dog). We created a “Social Interaction Scale” to define the interactions during these observations. Walking with a dog resulted in social interactions 63.3% of the time, compared to 39.9% while walking without a dog. Results showed that walking with a dog significantly increased social interaction (z-score of 4.9, p-value < 0.0001). From our analysis, we concluded that walking with a dog can promote social interaction. Further research is suggested to assess the effect of these facilitated social interactions on feelings of loneliness and psychosocial well-being.

A Tram Ride You Would Talk About

As an artist and junior researcher for the project “Public Transport as Public Space,” my aim is to understand atmospheres on urban public transport and the ways in which they can be changed through performative public art practice. Indefinite yet powerful, atmospheres, which emerge in the relation between a perceived environment and perceiving bodies (Böhme 2017), can be created deliberately through aesthetic work and used as a tool for shaping certain experiences and behaviors in public space (Allen 2006). For instance, visually attractive public artworks permanently integrated into the public transport environment may create atmospheres of safety and comfort, navigating passengers through this regulated public space. On the other hand, on public transport, where unacquainted people must travel shoulder to shoulder, different atmospheres emerge not only through material modifications but also through unexpected encounters and events (Bissell 2010). In this sense, performative public art interventions can intentionally “drum up the ambience” (Thibaud 2015) and imbue the atmosphere of commutes with elements that are surprising and out of the ordinary. This paper outlines some of my art projects, which aim to carefully disrupt casual rides on public transport by creating moments of strangeness and humor.

Greetings as a device to find out and establish the language of service encounters in multilingual settings

Service encounters at the counter are a social arena in which unacquainted people come to interact together, without a priori knowing the language of the other. In multilingual institutional settings, such as places where immigrants, mobile workers, cosmopolitan clients, and tourists gather to ask for services, this is a common configuration. These settings are exemplary for investigating how relevant linguistic resources are emergently discovered, negotiated, and established in the course of the interaction. Instead of supposing that shared linguistic resources are a necessary condition for social interaction to happen, the detailed analysis of these settings invites the researcher to study how participants orient to other available linguistic resources, identify and recognize them, and finally negotiate and select the appropriate and adjusted ones to progress within the encounter. Based on conversation analysis, the paper describes the opening of encounters as a locus where linguistic choices are guessed, checked, requested, and negotiated among participants. The main focus is on greetings, as a practice used to establish and possibly negotiate the language of the encounter. The data come from video recordings at two federal institutions in Switzerland – counters offering services at the border and at railway stations – considered exemplary sites for observing multilingual exchanges among customers and clerks.

Social profiling through image understanding: Personality inference using convolutional neural networks

The role of images in the last ten years has changed radically due to the advent of social networks: from media objects mainly used to communicate visual information, images have become personal, associated with the people that create or interact with them (for example, giving a “like”). Therefore, in the same way that a post reveals something of its author, so now the images associated to a person may embed some of her individual characteristics, such as her personality traits. In this paper, we explore this new level of image understanding with the ultimate goal of relating a set of image preferences to personality traits by using a deep learning framework. In particular, our problem focuses on inferring both self-assessed (how the personality traits of a person can be guessed from her preferred image) and attributed traits (what impressions in terms of personality traits these images trigger in unacquainted people), learning a sort of wisdom of the crowds. Our characterization of each image is locked within the layers of a CNN, allowing us to discover more entangled attributes (aesthetic patterns and semantic information) and to better generalize the patterns that identify a trait. The experimental results show that the proposed method outperforms state-of-the-art results and captures what visually characterizes a certain trait: using a deconvolution strategy we found a clear distinction of features, patterns and content between low and high values in a given trait.

Road Traffic Reduction via Implementation ofAndroid Based Carpooling Application

Carpooling (also known as car-sharing, ride-sharing and lift sharing), is the sharing of car journeys so that more than one person travels in a car. By having more one vehicle, carpooling reduces each person’s travels costs such as fuel costs, tolls, and the stress of driving. Carpooling is also seen as a more environmentally friendly and sustainable way to travel as sharing journeys reduces carbon emissions, traffic congestion on the roads, and the need for parking spaces. Authorities often encourage carpooling, especially during high pollution periods and high fuel prices. We intent on making an ANDROID based application that will enable to let people know if vehicles are available for carpool in their desired path they can sign in for it. This will enable people using this application to share expense, not worry about hiring a cab and making new connections. People having this application on their cell phone can easily carpool with unacquainted people without worrying about security.

Trust, distrust and lack of confidence of users in online social media-sharing communities

With the proliferation of online communities, the deployment of knowledge, skills, experiences and user generated content are generally facilitated among participant users. In online social media-sharing communities, the success of social interactions for content sharing and dissemination among completely unknown users depends on ‘trust’. Therefore, providing a satisfactory trust model to evaluate the quality of content and to recommend personalized trustworthy content providers is vital for a successful online social media-sharing community. Current research on trust prediction strongly relies on a web of trust, which is directly collected from users. However, the web of trust is not always available in online communities and, even when it is available, it is often too sparse to accurately predict the trust value between two unacquainted people. Moreover, most of the extant trust research studies have not paid attention to the importance of distrust, even though distrust is a distinct concept from trust with different impacts on behavior. In this paper, we adopt the concepts of ‘trust’, ‘distrust’, and ‘lack of confidence’ in social relationships and propose a novel unifying framework to predict trust and distrust as well as to distinguish the confidently-made decisions (trust or distrust) from lack of confidence without a web of trust. This approach uses interaction histories among users including rating data that is available and much denser than explicit trust/distrust statements (i.e. a web of trust).

Role of Computational Trust Models in Service Science

With the proliferation of online communities and Person-to-Person (P2P) online service markets, the deployment of knowledge, skills, experiences and user generated contents services are generally facilitated among service users and service providers. In online service markets where well-established intermediaries are often eliminated, the success of social interactions for service exchange among completely unknown users depends on ‘trust’ of a service user for a service provider. Therefore, providing a satisfactory trust model to evaluate the quality of services and to recommend personalized trustworthy service providers is vital for a successful online community and P2P online service market. However, finding trustworthy service providers for each individual user is challenging because of the lack of direct experiences and the subjective property of trust. In order to resolve the challenges, current research on trust prediction strongly relies on a web of trust, which is directly collected from users. However, the web of trust is not always available in online communities and, even when it is available, it is often too sparse to accurately predict the trust value between two unacquainted people. In this paper, we propose a computational trust model to predict trust connectivity based on service providers’ expertise (local trust from direct experiences and a reputation) and service users’ affinity for certain contexts (topics). The approach used item rating data that is available and much more dense than direct trust data. In experiments with a real-world dataset, we show that our model can predict trust connectivity with a high degree of accuracy. The proposed computational trust framework can be applied to any type of online communities or P2P online service markets with a rating system.

Do‐it‐yourself functionalized silicones part 1: basic methods for characterization of commercial products

AbstractConventional silicone fluids of varying composition, microstructure, and functionality are commercially available with a view to prepare films, elastomers, or resins. This paper is the first of a series of papers devoted to the synthesis, characterization, and application of vinyl and hydrido‐functionalized silicones. We present some basic analytical techniques useful to unacquainted people to fully characterize silicone fluids in terms of molar mass, purity, composition, structure, and functionality. Some commercial polymers were thus examined by size exclusion chromatography (SEC), from which molar masses were checked and compared with those from the provider (derived from viscosities). Two SEC‐derived techniques were used to confirm the perfect linearity of the chains. 1H and 29Si NMR spectrograms were recorded, from which chemical shifts gave the position of the functional groups (either at both chain‐ends or inside the chains) and from which intensities of the NMR signals provided quantitative data, namely number‐average molar mass Mn and contents of functional groups. In the final part, special emphasis is laid on the microstructure of the chains. Copyright © 2008 John Wiley & Sons, Ltd.

Street remarks, address rights and the urban female: Socio-linguistic politics of gender in Harare

This article explores and descriptionbes the socio-linguistic and cultural features of street remarks that take place between unacquainted people in the streets of Harare. Concern here is the male-to-female remarks. It seems that women receive more, and more vigorous, markers of public passage than men and they are less frequently the originators of such communicative markers. We argue that the markers are purposeful or intentional and that they are motivated by linguistic, socio-cultural and historical gender stereotypes and ideological constructs.