Disparity in spatial accessibility is strongly associated with growing inequalities among urban communities. Since improving levels of accessibility for certain communities can provide them with upward social mobility and address social exclusion and inequalities in cities, it is important to understand the nature and distribution of spatial accessibility among urban communities. To support decision-makers in achieving inclusion and fairness in policy interventions in cities, we present an open and data-driven framework to understand the spatial nature of accessibility to infrastructure among the different demographics. We find that accessibility to a wide range of infrastructure in any city (54 cities) converges to a Zipf’s law, suggesting that inequalities also appear proportional to growth processes in these cities. Then, assessing spatial inequalities among the socioeconomically clustered urban profiles for 10 of those cities, we find urban communities are distinctly segregated along social and spatial lines. We find low accessibility scores for populations who have a larger share of minorities, earn less and have a relatively lower number of individuals with a university degree. These findings suggest that the reproducible framework we propose may be instrumental in understanding processes leading to spatial inequalities and in supporting cities to devise targeted measures for addressing inequalities for certain underprivileged communities.

Throughout history, social movements have often been catalysts for radical societal change. In the past two decades, hashtag activism, the use of social media platforms for internet activism, has become a driving force behind the development of social movements across the world. In the field of social movements science, a large body of research has studied the role of hashtag activism for the formation of social movements, but less efforts have been allocated towards the study of the spatio-temporal relationship that exists between hashtag activism and political mobilization processes. In this study, a large geo-located social media dataset pertaining to the #JusticeForGeorgeFloyd social movement is used to quantify the spatio-temporal relationship between hashtag activism and physical protest activity. Results of this study indicate that at the national, state, and county scale, hashtag activism bears a strong positive temporal relationship with physical protest activity. Through the statistical modeling of this relationship, it is possible to predict the intensity of national, state, and county level protest activity on a given day based on the intensity of state and county level social movement related tweet counts the day before. At smaller scales (i.e. county), however, this research finds that the strength of this relationship is more variable, and it appears to be strongly dependent on population density. As such, this study reveals the existence of a critical population density threshold of 200 people/km2 , at which an increase in the number of social movement related tweets is likely to spark with an increase in the number of physical protests. These results represent novel insights that further contribute to our understanding of the complex spatio-temporal political mobilization processes that occur during social movements.

Disparity in spatial accessibility is strongly associated with growing inequalities among urban communities. Since improving levels of accessibility for certain communities can provide them with upward social mobility and address social exclusion and inequalities in cities, it is important to understand the nature and distribution of spatial accessibility among urban communities.To support decision-makers in achieving inclusion and fairness in policy interventions in cities, we present an open-source and data-driven framework to understand the spatial nature of accessibility to infrastructure among the different demographics. We find that accessibility to a wide range of infrastructure in any city (54 cities) converges to a Zipf's law, suggesting that inequalities also appear proportional to growth processes in these cities. Then, assessing spatial inequalities among the socioeconomically clustered urban profiles for 10 of those cities, we find urban communities are distinctly segregated along social and spatial lines. We find low accessibility scores for populations who have a larger share of minorities, earn less, and have a relatively lower number 1

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