Urban Computing and Mobile Devices

In this issue's Works in Progress department, we have 12 urban computing and mobile device entries that span a wide range of computing and social areas. The first entry examines how an urban environment could operate as a large-scale, real-time control system. One project focuses on annotating public spaces and sharing the tags with others. Two projects tie together social networking in cyberspace with local urban communities. Two projects examine computing and social interactions in physical spaces. Two entries explore how to combine synthetic and physical views of urban environments. Four entries investigate how we explore urban spaces, interact with technology in those spaces, and create shared community histories.     

Wired mobile phones: the case of community technology centers in favelas of Brazil*

ABSTRACT

The growing spread of mobile phones and internet has some practitioners and scholars arguing about the possible irrelevance of community technology centers (CTCs) serving low-income communities. However, although mobile internet is making great strides, it does not yet substitute for public access; in actuality, mobile phones and computers at CTCs complement each other in providing those who face digital inequalities with a broader sociotechnical experience. In order to explore this problem, this paper explores this experience by investigating how favela residents appropriate mobile phones, posing the question, “how do marginalized populations perceive CTCs in the mobile internet era?” To address this question, I draw on a 10-month ethnography in the favelas of Vitória, Brazil which examines slum residents’ uses of information and communication technologies (ICTs) such as computers and smartphones. Through this research, I demonstrate how marginalized people take advantage of smartphones and computers in a complementary way, using these ICTs to best meet their needs as they experience daily life in a relatively severe environment.     

Geographic ‘Place’ and ‘Community Information’ Preferences

People dynamically structure social interactions and activities at various locations in their environments in specialized types of places such as the office, home, coffee shop, museum and school. They also imbue various locations with personal meaning, creating group ‘hangouts’ and personally meaningful ‘places’. Mobile location-aware community systems can potentially utilize the existence of such ‘places’ to support the management of social information and interaction. However, acting effectively on this potential requires an understanding of how: (1) places and place-types relate to people’s desire for place-related awareness of and communication with others; and (2) what information people are willing to provide about themselves to enable place-related communication and awareness. We present here the findings from two qualitative studies, a survey of 509 individuals in New York, and a study of how mobility traces can be used to find people’s important places in an exploration of these questions. These studies highlight how people value and are willing to routinely provide information such as ratings, comments, event records relevant to a place, and when appropriate their location to enable services. They also suggest how place and place-type data could be used in conjunction with other information regarding people and places so that systems can be deployed that respect users’ People-to-People-to-Places data sharing preferences. We conclude with a discussion on how ‘place’ data can best be utilized to enable services when the systems in question are supported by a sophisticated computerized user-community social-geographical model.     

Analyzing public interventions through the lens of experimentalism: the case of the Museum of Random Memory

ABSTRACT

Over 30 computational scientists, designers, artists, and activists collaboratively performed eight Museum of Random Memory workshops and exhibitions from 2016 to 2018. Here, we explore how the framework of ‘experimentation’ helped us analyze our own iterative development of techniques to foster critical data literacy. After sketching key aspects of experimentation across disciplines, we detail moments within where researchers tweaked, observed, tested, reflected, and tweaked again. This included changing scale, format, and cultural context; observing how people responded to digital versus analog memory-making activities; modifying prompts to evoke different conversations among participants about how future memories might be imagined or read by future archeologists; and finding creative ways to discuss and trouble ethics of data sharing. We conclude that coopting some of the techniques typical in natural science laboratories can prompt scholar activists to continuously recalibrate their processes and adjust interactions as they build pedagogical strategies for fostering critical data literacy in the public sphere.     

Facebook communities about nostalgic photos of Turkey: creative practices of remembering and representing the past

ABSTRACT

This article focuses on Facebook communities about nostalgic photos of Turkey to explore how citizenship is enacted through the participatory and collaborative use of social media to remember and represent the past. By sharing their personal photos, knowledge, testimonies, narratives and life stories, members of these communities actively and creatively use social media to generate new ways of remembering and representing the past, as well as improving its accessibility and visibility. Furthermore, through exchanging affectively and politically charged photos and conversations about the past, participants fashion nostalgia as a public feeling that becomes a source for affective political criticism of the present. This article addresses the participatory and collaborative creation of knowledge and memory of the past to discuss everyday creative citizenship practices facilitated by social media.     

Adaptive notifications to support knowledge sharing in close-knit virtual communities

Social web-groups where people with common interests and goals communicate, share resources, and construct knowledge, are becoming a major part of today’s organisational practice. Research has shown that appropriate support for effective knowledge sharing tailored to the needs of the community is paramount. This brings a new challenge to user modelling and adaptation, which requires new techniques for gaining sufficient understanding of a virtual community (VC) and identifying areas where the community may need support. The research presented here addresses this challenge presenting a novel computational approach for community-tailored support underpinned by organisational psychology and aimed at facilitating the functioning of the community as a whole (i.e. as an entity). A framework describing how key community processes—transactive memory (TM), shared mental models (SMMs), and cognitive centrality (CCen)—can be utilised to derive knowledge sharing patterns from community log data is described. The framework includes two parts: (i) extraction of a community model that represents the community based on the key processes identified and (ii) identification of knowledge sharing behaviour patterns that are used to generate adaptive notifications. Although the notifications target individual members, they aim to influence individuals’ behaviour in a way that can benefit the functioning of the community as a whole. A validation study has been performed to examine the effect of community-adapted notifications on individual members and on the community as a whole using a close-knit community of researchers sharing references. The study shows that notification messages can improve members’ awareness and perception of how they relate to other members in the community. Interesting observations have been made about the linking between the physical and the VC, and how this may influence members’ awareness and knowledge sharing behaviour. Broader implications for using log data to derive community models based on key community processes and generating community-adapted notifications are discussed.     

Why would online gamers share their innovation-conducive knowledge in the online game user community? Integrating individual motivations and social capital perspectives

The user community has been an important external source of a firm’s product or service innovation. Users’ innovation-conducive knowledge sharing enables the community to work as a vital source of innovation. But, traditional economic theories of innovation seem to provide few explanations about why such knowledge sharing takes place for free in the user community. Therefore, this study investigates what drives community users to freely share their innovation-conducive knowledge, using the theory of planned behavior. Based on an empirical analysis of the data from 1244 members of a South Korean online game user community, it reveals that intrinsic motivation, shared goals, and social trust are salient factors in promoting users’ innovation-conducive knowledge sharing. Extrinsic motivation and social tie, however, were found to affect such sharing adversely, contingent upon whether a user is an innovator or a non-innovator. The study illustrates how social capital, in addition to individual motivations, forms and influences users’ innovation-conducive knowledge sharing in the online gaming context.     

This is not classified: everyday information seeking and encountering in smart urban spaces

We present a multipronged comparative study of citizens’ self-proclaimed information needs and actual information seeking behavior in smart urban spaces. We first conducted several user studies to identify the types of information services that citizens believed to be useful in urban setting utilizing methods ranging from contextual inquiry with lo-fi prototypes to “card sorting” exercise with a separate set of participants, and finally to implementing selected services. We then made a sizeable constructive intervention into the urban space by deploying in a city center 12 large, interactive public displays called “hotspots” to offer a wide range of previously identified information services. We collected comprehensive qualitative and quantitative data on the usage of the hotspots and their services by the general public during 13 months. Our study reveals discrepancies between a priori and a posteriori information seeking strategies extracted from the self-proclaimed information needs and the actual usage of the hotspots.     

A machine learning-based method for the large-scale evaluation of the qualities of the urban environment

Given the present size of modern cities, it is beyond the perceptual capacity of most people to develop a good knowledge about the qualities of the urban space at every street corner. Correspondingly, for planners, it is also difficult to accurately answer questions such as ‘where the quality of the physical environment is the most dilapidated in the city that regeneration should be given first consideration’ and ‘in fast urbanising cities, how is the city appearance changing’. To address this issue, in the present study, we present a computer vision method that contains three machine learning models for the large-scale and automatic evaluation on the qualities of the urban environment by leveraging state-of-the-art machine learning techniques and wide-coverage street view images. From various physical qualities that have been identified by previous research to be important for the urban visual experience, we choose two key qualities, the construction and maintenance quality of building facade and the continuity of street wall, to be measured in this research. To test the validity of the proposed method, we compare the machine scores with public rating scores collected on-site from 752 passers-by at 56 locations in the city. We show that the machine learning models can produce a medium-to-good estimation of people's real experience, and the modelling results can be applied in many ways by researchers, planners and local residents.     

Future access to essential services in a growing smart city: The case of Surrey,British Columbia

The concept of accessibility – the ease with which people can reach places or opportunities –lies at the heart of what makes cities livable, workable and sustainable. As urban populations shift over time, predicting the changes to accessibility demand for certain services becomes crucial for responsible and ‘smart’ urban planning and infrastructure investment. In this study, we investigate how projected population change could affect accessibility to essential services in the City of Surrey, one of the fastest growing cities in Canada. Our objectives are two-fold: first, to quantify the additional pressure that Surrey's growing population will have on existing facilities; second, to investigate how changes in the spatial distribution of different age and income groups will impact accessibility equity across the city. We evaluated accessibility levels to healthcare facilities and schools across Surrey's multimodal transport network using origin-destination matrices, and combined this information with high-resolution longitudinal census data. Paying close attention to two vulnerable population groups – children and youth (0–19 years of age) and seniors (65+ years of age) – we analyzed shifts in accessibility demand from 2016 to 2022. The results show that population growth both within and outside the catchments of existing facilities will have varying implications for future accessibility demand in different areas of the city. By 2022, the city's hospitals and walk-in clinics will be accessible to ~9000 and ~124,000 more people (respectively) within a predefined threshold of 30 min by public transport. Schools will also face increased demand, as ~8000 additional children/youth in 2022 will move to areas with access to at least half of the city's schools. Conversely, over 27,000 more people – almost half of them seniors – will not be able to access a hospital in under 30 min by 2022. Since low-income and senior residents moving into poorly connected areas tend to be more reliant on public transport, accessibility equity may decline in some rural communities. Our study highlights how open-source data and code can be leveraged to conduct in-depth analysis of accessibility demand across a city, which is key for ensuring inclusive and ‘smart’ urban investment strategies.     

Individuals among commuters: Building personalised transport information services from fare collection systems

This work investigates how data from public transport fare collection systems can be used to analyse travellers’ behaviour, and transform travel information systems that urban residents use to navigate their city into personalised and dynamic systems that cater for each passenger’s unique needs. In particular, we show how fare collection data can be used to identify behavioural differences between passengers: we thus advocate for a personalised approach to delivering transport related information to travellers. To demonstrate the potential for personalisation we compute trip time estimates that more accurately reflect the travel habits of each passenger. We propose a number of algorithms for personalised trip time estimations, and empirically demonstrate that these approaches outperform both a non-personalised baseline computed from the data, as well as published travel times as currently offered by the transport authority. Furthermore, we show how to easily scale the system by pre-clustering travellers. We close by outlining the wide variety of applications and services that may be fuelled by fare collection data.     

Online-Literaturdatenbanken im Bereich der Wirtschaftsinformatik: Bereitstellung wissenschaftlicher Literatur und Analyse von Interaktionen der Wissensteilung

Knowledge sharing is fundamental for innovations in the scientific community. The paper examines how the interaction of knowledge sharing is supported by online services. With respect to business information systems, a survey of online literature databases is given, providing an aggregation of various publication sources, a direct access to publications, and which are available to the public. Furthermore, special analysis services are presented which describe competitive interactions of knowledge sharing via rankings on the one hand, and cooperative interactions of knowledge sharing via co-authorship evaluation on the other.     

Implicit: a multi-agent recommendation system for web search

For people with non-ordinary interests, it is hard to search for information on the Internet because search engines are impersonalized and are more focused on “average” individuals with “standard” preferences. In order to improve web search for a community of people with similar but specific interests, we propose to use the implicit knowledge contained in the search behavior of groups of users. We developed a multi-agent recommendation system called Implicit, which supports web search for groups or communities of people. In Implicit, agents observe behavior of their users to learn about the “culture” of the community with specific interests. They facilitate sharing of knowledge about relevant links within the community by means of recommendations. The agents also recommend contacts, i.e., who in the community is the right person to ask for a specific topic. Experimental evaluation shows that Implicit improves the quality of the web search in terms of precision and recall.     

Physical, Social, and Experiential Knowledge in Pervasive Computing Environments

Pervasive computing designers and researchers often create services and applications to help people record their experiences. At the same time, cheap, small, and easy-to-deploy recording technologies are quickly emerging throughout public spaces. In many ways, these technologies are pervasive computing realized. Understanding how people deal with audio and video recording is therefore a good way to explore how people might adopt, adapt, and react to pervasive computing technologies in general. A long-term deployment of a system for recording experiences in informal spaces demonstrates that people use physical, social, and experiential knowledge to determine new technologies' relative utility and safety. In this paper, we aim to add significantly to the research surrounding security and privacy concerns by focusing on them rather than just noting them as a side effect of testing an application's utility and usability.     

Uncovering inconspicuous places using social media check-ins and street view images

There is a Chinese proverb, “if your wine tastes really good, you do not need to worry about the location of your bar (酒香不怕巷子深)”, which implies that the popular places for local residents are sometimes hidden behind an unassuming door or on unexpected streets. Discovering these unassuming places (e.g. restaurants) of a city will benefit the understanding of local culture and help to build livable neighborhoods. Previous work has been limited by the lack of appropriate data sources and efficient tools to evaluate the popularity, ambiance and physical surroundings of places in large-scale urban areas. In addition, how to characterize places with respect to different groups of people remains unclear. In this work, we propose a data-driven approach using social media check-ins and street-level images to compare the different activity patterns of visitors and locals, and uncover inconspicuous but interesting places for them in a city. We use check-in records as a proxy of the popularity of a particular type of place, and differentiate visitors and locals based on their travel and social media behaviors. In addition, we employ street-level images to represent the physical environments of places. As a result, we discovered a number of inconspicuous yet popular restaurants in Beijing. These restaurants are located mostly in deep alleys of Old Beijing neighborhoods, where the physical environments are not particularly appealing; however, these places are frequently visited by locals for social engagements. We also discovered beautiful but unpopular outdoor places in Beijing. These places are potential recreational areas for all groups of people and could be improved regarding urban design and planning to make these public infrastructures more attractive. This work demonstrates how multi-source big geo-data can be combined to build comprehensive place-based representations for different groups of people.     

对“平安城市”建设及信息化实施方略的研究

对于任何一个城市来说,经济的发展程度不能决定其现代化水平,让城市居民拥有高度的安全感和信任感对于文明城市的建设至关重要。伴随着改革开放脚步的不断加快和城市化水平的不断提高,高新技术产业渗透到各行各业,信息化时代到来。作为人民群众的生命财产安全的守护者,公安信息化的发展对于"平安城市"的建设发挥着不可小觑的作用。     

Local News Chatter: Augmenting Community News by Aggregating Hyperlocal Microblog Content in a Tag Cloud

Being aware of local community information is critical to maintaining civic engagement and participation. The use of online news and microblog content to create and disseminate community information has long been studied. However, interactions in the online spaces dedicated to local communities tend to only garner very limited usage, and people often do not consider microblog content as a meaningful source of local community information. Local News Chatter (LNC) was designed to address these challenges by augmenting local news feeds with microblog content and presenting them in a tag cloud that displays news topics of varying popularity with different tag sizes. Our study with 30 local residents highlights that LNC increases the visibility of hyperlocal community news information and successfully utilizes microblog as an additional information layer. LNC also increases one’s community awareness and shows the potential for leveraging community knowledge as a deliberation platform for local topics.     

Exploring factors that influence knowledge sharing behavior via weblogs

Knowledge sharing is seen as one of the essential processes for knowledge management. A growing number of professionals have started weblogging, and use this tool to share their ideas. It is important to explore ways to encourage individuals to contribute personal knowledge and to assist community members to share their expertise. Through the lens of sharing culture, we explore the factors that facilitate voluntary knowledge sharing in a virtual community. Specifically, the use of three categories associated with a sharing culture – fairness, identification and openness – is considered as a linear combination, which means that enjoying helping and usefulness/relevancy thereafter promote knowledge sharing behavior. To test the theoretical model, we survey 442 members of three online communities. In addition to the positive effects of fairness and openness on community sharing culture, we also find that enjoying helping, sharing culture and usefulness/relevancy are strongly linked to member knowledge sharing behavior. This paper offers a new perspective on the mechanisms related to the sharing culture construct, which in turn facilitates weblog knowledge sharing behaviors and yields important implications for understanding knowledge sharing behavior in online communities.     

Publicly Private and Privately Public: Social Networking on YouTube

YouTube is a public video-sharing website where people can experience varying degrees of engagement with videos, ranging from casual viewing to sharing videos in order to maintain social relationships. Based on a one-year ethnographic project, this article analyzes how YouTube participants developed and maintained social networks by manipulating physical and interpretive access to their videos. The analysis reveals how circulating and sharing videos reflects different social relationships among youth. It also identifies varying degrees of "publicness" in video sharing. Some participants exhibited "publicly private" behavior, in which video makers' identities were revealed, but content was relatively private because it was not widely accessed. In contrast, "privately public" behavior involved sharing widely accessible content with many viewers, while limiting access to detailed information about video producers' identities.     

Preventing Youth Pregnancy: Dialogue and Deliberation in a Science Museum Exhibit

ABSTRACT

In this article, we explore how visitors engage with a science museum exhibit that displays controversial topics. Through a case study methodology, we focus on the Brazilian exhibit Preventing Youth Pregnancy that delves into teen pregnancy, sexual practices, and sexually transmitted diseases. Using the lens of science communication (an emergent field of research) we explore (a) communication patterns established between the exhibit and the public and (b) the dimensions of engagement that visitors experienced. Data were collected through observations and interviews with visitors, field notes, exit comment cards, and interviews with staffers. Our findings revealed the potential of articulating different models of science communication and exposed a visitor experience in which informed decision making, sharing of personal stories, co-production of knowledge, and learning how to care (and act) were at play while negotiating the complexities of the issues raised by the displays.