Understanding trends and drivers of urban poverty in American cities

Urban poverty arises from the uneven distribution of poor populations across neighborhoods of a city. We study the trend and drivers of urban poverty across American cities over the last 40 years. To do so, we resort to a family of urban poverty indices that account for features of incidence, distribution, and segregation of poverty across census tracts. Compared to the universally-adopted concentrated poverty index, these measures have a solid normative background. We use tract-level data to assess the extent to which demographics, housing, education, employment, and income distribution affect levels and changes in urban poverty. A decomposition study allows to single out the effect of changes in the distribution of these variables across cities from changes in their correlation with urban poverty. We find that demographics and income distribution have a substantial role in explaining urban poverty patterns, whereas the same effects remarkably differ when using the concentrated poverty indices

Diffusion of Lexical Change in Social Media

Computer-mediated communication is driving fundamental changes in the nature of written language. We investigate these changes by statistical analysis of a dataset comprising 107 million Twitter messages (authored by 2.7 million unique user accounts). Using a latent vector autoregressive model to aggregate across thousands of words, we identify high-level patterns in diffusion of linguistic change over the United States. Our model is robust to unpredictable changes in Twitter's sampling rate, and provides a probabilistic characterization of the relationship of macro-scale linguistic influence to a set of demographic and geographic predictors. The results of this analysis offer support for prior arguments that focus on geographical proximity and population size. However, demographic similarity -- especially with regard to race -- plays an even more central role, as cities with similar racial demographics are far more likely to share linguistic influence. Rather than moving towards a single unified "netspeak" dialect, language evolution in computer-mediated communication reproduces existing fault lines in spoken American English.Comment: preprint of PLOS-ONE paper from November 2014; PLoS ONE 9(11) e11311

Smart Cities MOOC: Teaching citizens how to co-create smart cities

There is increasing recognition that the ICT4S community needs to take a role in both developing education and conducting re-search on how to educate people in using ICT to make urban areas more sustainable. In this paper we explore the question how can a Massive Open Online Course (MOOC) be used to engage citizens in learning about smart cities and teach them how to co-create a smart cities project in their community. We discuss our experiences of designing and delivering a Smart Cities MOOC, a multidisciplinary course targeted at an international audience and built upon the pedagogical approach of social learning that is supported through FutureLearn, the MOOC platform on which the course is delivered. We use data gathered from the first presentation of the course to evaluate the motivations, demographics, online participation and experiences of our learners. An analysis of social learning interactions also provides insight into citizens’ views on smart cities and we identify how the MOOC can be adapted to meet the learning needs of smart city initiatives and potential areas for future research

Community Development in Dynamic Neighborhoods: Synchronizing Services and Strategies with Immigrant Communities

Community development organizations must be increasingly cognizant of and responsive to their changing neighborhoods. Major demographic factors related to the growth and influx of recent immigrants to the United States are having a notable impact on many communities. Through a review of current research and interviews with leading experts and practitioners of community development organizations, private lenders and governmental agencies, this analysis explores (1) the importance of immigrants in community development, (2) the response of community development organizations to recent demographic shifts, and (3) the challenges and opportunities practitioners face when connecting immigrants to their communities.Despite growing research about the implications of immigrant markets for the private sector, there is little research about the role and contributions of community development organizations in the integration of new immigrants. Immigration trends and characteristics are different today than those of the late nineteenth and early twentieth centuries. This research concludes that these new demographics drive much of the dynamic change in cities across the United States. CDOs can best address the changes at the local level, but need more data and market analysis of neighborhood trends. These organizations are in a key position to connect newcomers not only to long-term housing, but also to business development, jobs and leadership opportunities through strategic partnerships and planning

Using Social Media to Promote STEM Education: Matching College Students with Role Models

STEM (Science, Technology, Engineering, and Mathematics) fields have become increasingly central to U.S. economic competitiveness and growth. The shortage in the STEM workforce has brought promoting STEM education upfront. The rapid growth of social media usage provides a unique opportunity to predict users' real-life identities and interests from online texts and photos. In this paper, we propose an innovative approach by leveraging social media to promote STEM education: matching Twitter college student users with diverse LinkedIn STEM professionals using a ranking algorithm based on the similarities of their demographics and interests. We share the belief that increasing STEM presence in the form of introducing career role models who share similar interests and demographics will inspire students to develop interests in STEM related fields and emulate their models. Our evaluation on 2,000 real college students demonstrated the accuracy of our ranking algorithm. We also design a novel implementation that recommends matched role models to the students.Comment: 16 pages, 8 figures, accepted by ECML/PKDD 2016, Industrial Trac

Bridging the Gap: Credit Scores and Economic Opportunity in Illinois Communities of Color

This report analyzed credit score data from a major national credit bureau in large Illinois zip codes and found significant disparities in credit characteristics between communities of color and predominantly white communities, as well as between major metropolitan areas and non-metropolitan areas. The report explains the importance of credit scores and how they are used, and recommends several policies to improve economic opportunity for people and communities impacted by low credit scores. Included is an appendix with demographics and credit score averages and distributions for large Illinois zip codes

The Perceived Role of High-Level Black Urban Managers in Virginia

Focusing on sixteen cities in Virginia, the researcher studied the perceived managerial and career roles that high level black urban managers play in local government. From June to August 1991, black managers in the study completed self-assessments in the following areas: (1) socio-demographics, (2) perceived managerial and career role, (3) behaviors associated with managerial activism, pursuing the needs of the black community and career development, and (4) characteristics of their work environment. Based on their responses, the managers were assigned to role groups. Differences among the groups were noted. The entrepreneurs reported a higher degree of organizational support, role norm and congruence, and pursued the needs of the black community. The climbers engaged in career strategy behaviors. In addition, supervisory support was related to career role. The researcher concludes that specific organizational and personal factors are related to the managerial and career roles black managers play in the urban environment

Urban Dreams of Migrants: A Case Study of Migrant Integration in Shanghai

Unprecedented human mobility has driven the rapid urbanization around the world. In China, the fraction of population dwelling in cities increased from 17.9% to 52.6% between 1978 and 2012. Such large-scale migration poses challenges for policymakers and important questions for researchers. To investigate the process of migrant integration, we employ a one-month complete dataset of telecommunication metadata in Shanghai with 54 million users and 698 million call logs. We find systematic differences between locals and migrants in their mobile communication networks and geographical locations. For instance, migrants have more diverse contacts and move around the city with a larger radius than locals after they settle down. By distinguishing new migrants (who recently moved to Shanghai) from settled migrants (who have been in Shanghai for a while), we demonstrate the integration process of new migrants in their first three weeks. Moreover, we formulate classification problems to predict whether a person is a migrant. Our classifier is able to achieve an F1-score of 0.82 when distinguishing settled migrants from locals, but it remains challenging to identify new migrants because of class imbalance. This classification setup holds promise for identifying new migrants who will successfully integrate into locals (new migrants that misclassified as locals).Comment: A modified version. The paper was accepted by AAAI 201

Doing More For More: Hispanic Issues for Texas and the Nation

Hogg Foundation for Mental Healt