scholarly journals Twitter and Census Data Analytics to Explore Socioeconomic Factors for Post-COVID-19 Reopening Sentiment

2020 ◽  
Author(s):  
Md. Mokhlesur Rahman ◽  
G.G.M.N. Ali ◽  
Xue Jun Li ◽  
Kamal Chandra Paul ◽  
P. H.J. Chong
Keyword(s):  
Low Income ◽  
Logit Model ◽  
Goodness Of Fit ◽  
Census Data ◽  
The United States ◽  
Socioeconomic Factor ◽  
Economic Downturn ◽  
Twitter Data ◽  
The People ◽  
Education Levels

Investigating and classifying sentiments of social media users (e.g., positive, negative) towards an item, situation, and system are very popular among the researchers. However, they rarely discuss the underlying socioeconomic factor associations for such sentiments. This study attempts to explore the factors associated with positive and negative sentiments of the people about reopening the economy, in the United States (US) amidst the COVID-19 global crisis. It takes into consideration the situational uncertainties (i.e., changes in work and travel pattern due to lockdown policies), economic downturn and associated trauma, and emotional factors such as depression. To understand the sentiment of the people about the reopening economy, Twitter data was collected, representing the 51 states including Washington DC of the US. State-wide socioeconomic characteristics of the people (e.g., education, income, family size, and employment status), built environment data (e.g., population density), and the number of COVID-19 related cases were collected and integrated with Twitter data to perform the analysis. A binary logit model was used to identify the factors that influence people toward a positive or negative sentiment. The results from the logit model demonstrate that family households, people with low education levels, people in the labor force, low-income people, and people with higher house rent are more interested in reopening the economy. In contrast, households with a high number of members and high income are less interested to reopen the economy. The accuracy of the model is good (i.e., the model can correctly classify 56.18\% of the sentiments). The Pearson chi2 test indicates that overall this model has high goodness-of-fit. This study provides a clear indication to the policymakers where to allocate resources and what policy options they can undertake to improve the socioeconomic situations of the people and mitigate the impacts of pandemics in the current situation and as well as in the future.

scholarly journals Twitter and Census Data Analytics to Explore Socioeconomic Factors for Post-COVID-19 Reopening Sentiment

2020 ◽  
Author(s):  
Md. Mokhlesur Rahman ◽  
G. G. Md. Nawaz Ali ◽  
Xue Jun Li ◽  
Kamal Chandra Paul ◽  
Peter H.J. Chong
Keyword(s):  
Low Income ◽  
Logit Model ◽  
Goodness Of Fit ◽  
Census Data ◽  
The United States ◽  
Socioeconomic Factor ◽  
Economic Downturn ◽  
Twitter Data ◽  
The People ◽  
Education Levels

Investigating and classifying sentiments of social media users (e.g., positive, negative) towards an item, situation, and system are very popular among the researchers. However, they rarely discuss the underlying socioeconomic factor associations for such sentiments. This study attempts to explore the factors associated with positive and negative sentiments of the people about reopening the economy, in the United States (US) amidst the COVID-19 global crisis. It takes into consideration the situational uncertainties (i.e., changes in work and travel pattern due to lockdown policies), economic downturn and associated trauma, and emotional factors such as depression. To understand the sentiment of the people about the reopening economy, Twitter data was collected, representing the 51 states including Washington DC of the US. State-wide socioeconomic characteristics of the people (e.g., education, income, family size, and employment status), built environment data (e.g., population density), and the number of COVID-19 related cases were collected and integrated with Twitter data to perform the analysis. A binary logit model was used to identify the factors that influence people toward a positive or negative sentiment. The results from the logit model demonstrate that family households, people with low education levels, people in the labor force, low-income people, and people with higher house rent are more interested in reopening the economy. In contrast, households with a high number of members and high income are less interested to reopen the economy. The accuracy of the model is good (i.e., the model can correctly classify 56.18\% of the sentiments). The Pearson chi2 test indicates that overall this model has high goodness-of-fit. This study provides a clear indication to the policymakers where to allocate resources and what policy options they can undertake to improve the socioeconomic situations of the people and mitigate the impacts of pandemics in the current situation and as well as in the future.

scholarly journals Twitter and Census Data Analytics to Explore Socioeconomic Factors for Post-COVID-19 Reopening Sentiment

2020 ◽  
Author(s):  
Md. Mokhlesur Rahman ◽  
G. G. Md. Nawaz Ali ◽  
Xue Jun Li ◽  
Kamal Chandra Paul ◽  
Peter H.J. Chong
Keyword(s):  
Low Income ◽  
Logit Model ◽  
Goodness Of Fit ◽  
Census Data ◽  
The United States ◽  
Socioeconomic Factor ◽  
Economic Downturn ◽  
Twitter Data ◽  
The People ◽  
Education Levels

AbstractInvestigating and classifying sentiments of social media users (e.g., positive, negative) towards an item, situation, and system are very popular among the researchers. However, they rarely discuss the underlying socioeconomic factor associations for such sentiments. This study attempts to explore the factors associated with positive and negative sentiments of the people about reopening the economy, in the United States (US) amidst the COVID-19 global crisis. It takes into consideration the situational uncertainties (i.e., changes in work and travel pattern due to lockdown policies), economic downturn and associated trauma, and emotional factors such as depression. To understand the sentiment of the people about the reopening economy, Twitter data was collected, representing the 51 states including Washington DC of the US. State-wide socioeconomic characteristics of the people (e.g., education, income, family size, and employment status), built environment data (e.g., population density), and the number of COVID-19 related cases were collected and integrated with Twitter data to perform the analysis. A binary logit model was used to identify the factors that influence people toward a positive or negative sentiment. The results from the logit model demonstrate that family households, people with low education levels, people in the labor force, low-income people, and people with higher house rent are more interested in reopening the economy. In contrast, households with a high number of members and high income are less interested to reopen the economy. The accuracy of the model is good (i.e., the model can correctly classify 56.18% of the sentiments). The Pearson chi2 test indicates that overall this model has high goodness-of-fit. This study provides a clear indication to the policymakers where to allocate resources and what policy options they can undertake to improve the socioeconomic situations of the people and mitigate the impacts of pandemics in the current situation and as well as in the future.

scholarly journals Advertising photography during the 1930s: Victor Keppler's strike cigarette campaign

2021 ◽  
Author(s):  
Loreto Pinochet
Keyword(s):  
Low Income ◽  
The United States ◽  
Financial Resources ◽  
Budget Cuts ◽  
Advertising Agency ◽  
The Great Depression ◽  
The People ◽  
Print Advertisement ◽  
Colour Photography ◽  
The Masses

The Great Depression was a decade in the United States which was characterized by high unemployment, budget cuts and low income. Citizens, especially the working class did not have the financial resources to purchase the same amount of goods previous to this economic crisis. The advertising business took this opportunity to sell products to the masses, during a time when purchasing luxury goods were not a priority or even a possibility. This created many changes in how advertisements were produced and how they looked. Using Victor Keppler as an example, this thesis will describe how the advertising agency Lord & Thomas used colour photography for their Lucky Strike cigarette advertisement campaign, the Witnessed Statement Series. It will describe how the colour carbro print became the mass reproduced advertisement found in magazines and newspapers. The thesis will describe this process and the people who were involved in creating the final print advertisement.

scholarly journals Exploring longitudinal associations between neighborhood disadvantage and cortisol levels in early childhood

2017 ◽  
Vol 29 (5) ◽  
pp. 1649-1662 ◽  
Author(s):  
Eric D. Finegood ◽  
Jason R. D. Rarick ◽  
Clancy Blair ◽  
Keyword(s):  
Hpa Axis ◽  
Low Income ◽  
Salivary Cortisol ◽  
Multilevel Models ◽  
Census Data ◽  
Well Being ◽  
Neighborhood Disadvantage ◽  
The United States ◽  
Neighborhood Context ◽  
Cortisol Levels

AbstractChildren who grow up in poverty are more likely to experience chronic stressors that generate “wear” on stress regulatory systems including the hypothalamus–pituitary–adrenal (HPA) axis. This can have long-term consequences for health and well-being. Prior research has examined the role of proximal family and home contributions to HPA axis functioning. However, there is evidence to suggest that more distal levels of context, including neighborhoods, also matter. Prior evidence has primarily focused on adolescents and adults, with little evidence linking the neighborhood context with HPA activity in infancy and toddlerhood. We tested whether neighborhood disadvantage (indexed by US Census data) was associated with basal salivary cortisol levels at 7, 15, and 24 months of child age in a large sample of families (N = 1,292) residing in predominately low-income and rural communities in the United States. Multilevel models indicated that neighborhood disadvantage was positively associated with salivary cortisol levels and that this effect emerged across time. This effect was moderated by the race/ethnicity of children such that the association was only observed in White children in our sample. Findings provide preliminary evidence that the neighborhood context is associated with stress regulation during toddlerhood, elucidating a need for future work to address possible mechanisms.

scholarly journals Standardizing the fee-waiver application increased naturalization rates of low-income immigrants

2019 ◽  
Vol 116 (34) ◽  
pp. 16768-16772
Author(s):  
Vasil Yasenov ◽  
Michael Hotard ◽  
Duncan Lawrence ◽  
Jens Hainmueller ◽  
David D. Laitin
Keyword(s):  
Low Income ◽  
Service Providers ◽  
The United States ◽  
Immigrant Integration ◽  
Foreign Born ◽  
The Us ◽  
Before And After ◽  
Education Levels ◽  
Immigration Service ◽  
The Impact

Citizenship can accelerate immigrant integration and result in benefits for both local communities and the foreign-born themselves. Yet the majority of naturalization-eligible immigrants in the United States do not apply for citizenship, and we lack systematic evidence on policies specifically designed to encourage take-up. In this study, we analyze the impact of the standardization of the fee-waiver process in 2010 by the US Citizenship and Immigration Service (USCIS). This reform allowed low-income immigrants eligible for citizenship to use a standardized form to have their application fee waived. We employ a difference-in-differences methodology, comparing naturalization behavior among eligible and ineligible immigrants before and after the policy change. We find that the fee-waiver reform increased the naturalization rate by 1.5 percentage points. This amounts to about 73,000 immigrants per year gaining citizenship who otherwise would not have applied. In contrast to previous research on the take-up of federal benefits programs, we find that the positive effect of the fee-waiver reform was concentrated among the subgroups of immigrants with lower incomes, language skills, and education levels, who typically face the steepest barriers to naturalization. Further evidence suggests that this pattern is driven by immigration service providers, who are well-positioned to help the most needy immigrants file their fee-waiver requests.

Racial composition and trajectories of gentrification in the United States

Urban Studies ◽  
2020 ◽  
pp. 004209802096385
Author(s):  
Zawadi Rucks-Ahidiana
Keyword(s):  
Low Income ◽  
Census Data ◽  
The United States ◽  
Racial Composition ◽  
Lower Income ◽  
Middle Income ◽  
Predominately White ◽  
Racial Change ◽  
Racial Demographics ◽  
Black And Latino

Prior studies suggest that middle-income Americans are more likely to move to predominately white, low-income neighbourhoods than predominately black or Latino neighbourhoods. Given that black and Latino neighbourhoods are, on average, lower income and higher in poverty than low-income, white neighbourhoods, it may be that gentrification in these neighbourhoods is a different kind of change than that occurring in predominately white neighbourhoods. Using Census data from 1970 to 2010 for 275 Metropolitan Statistical Areas, I find that racial composition influences not only whether gentrification occurs, but how it occurs and whether it influences racial demographics. Majority white gentrifying tracts were more likely to experience an increase in higher-income residents and white residents, while majority non-white gentrifying tracts experienced an increase in higher-educated but not higher-income residents, and an increase in white residents and decrease in black and Latino residents. Racial composition thus contributed to the kind of gentrification that a tract experienced and the extent to which gentrification produced racial change. These findings suggest that race affects not only where gentrification occurs, as previously established, but also the kind of class and racial changes a neighbourhood experiences. Ultimately, this article suggests that gentrification neither unfolds in one way nor affects all neighbourhoods the same way.

Demonstrating Nutrient Cost Gradients: A Brooklyn Case Study

2014 ◽  
Vol 84 (5-6) ◽  
pp. 244-251 ◽  
Author(s):  
Robert J. Karp ◽  
Gary Wong ◽  
Marguerite Orsi
Keyword(s):  
Low Income ◽  
Energy Content ◽  
Food Selection ◽  
The United States ◽  
United States Department ◽  
Micronutrient Deficiencies ◽  
Caloric Density ◽  
Low Income Families ◽  
The Cost ◽  
The Impact

Abstract. Introduction: Foods dense in micronutrients are generally more expensive than those with higher energy content. These cost-differentials may put low-income families at risk of diminished micronutrient intake. Objectives: We sought to determine differences in the cost for iron, folate, and choline in foods available for purchase in a low-income community when assessed for energy content and serving size. Methods: Sixty-nine foods listed in the menu plans provided by the United States Department of Agriculture (USDA) for low-income families were considered, in 10 domains. The cost and micronutrient content for-energy and per-serving of these foods were determined for the three micronutrients. Exact Kruskal-Wallis tests were used for comparisons of energy costs; Spearman rho tests for comparisons of micronutrient content. Ninety families were interviewed in a pediatric clinic to assess the impact of food cost on food selection. Results: Significant differences between domains were shown for energy density with both cost-for-energy (p < 0.001) and cost-per-serving (p < 0.05) comparisons. All three micronutrient contents were significantly correlated with cost-for-energy (p < 0.01). Both iron and choline contents were significantly correlated with cost-per-serving (p < 0.05). Of the 90 families, 38 (42 %) worried about food costs; 40 (44 %) had chosen foods of high caloric density in response to that fear, and 29 of 40 families experiencing both worry and making such food selection. Conclusion: Adjustments to USDA meal plans using cost-for-energy analysis showed differentials for both energy and micronutrients. These differentials were reduced using cost-per-serving analysis, but were not eliminated. A substantial proportion of low-income families are vulnerable to micronutrient deficiencies.

Religion and Mythology in the Chilembwe Rising of 1915 in Nyasaland and the Easter Rising of 1916 in Ireland: Preparing for the End Times?

2017 ◽  
Vol 23 (1) ◽  
pp. 51-66
Author(s):  
T. Jack Thompson
Keyword(s):  
The United States ◽  
Religious Motivation ◽  
Easter Rising ◽  
British Rule ◽  
The People ◽  
Head Of State ◽  
Interesting Difference ◽  
Racial Injustice ◽  
Book Of Daniel ◽  
End Times

Superficially there are many parallels between the Chilembwe Rising of 1915 in Nyasaland and the Easter Rising of 1916 in Ireland – both were anti-colonial rebellions against British rule. One interesting difference, however, occurs in the way academics have treated John Chilembwe, leader of the Nyasaland Rising, and Patrick Pearse, one of the leaders of the Irish Rising and the man who was proclaimed head of state of the Provisional government of Ireland. For while much research on Pearse has dealt with his religious ideas, comparatively little on Chilembwe has looked in detail at his religious motivation – even though he was the leader of an independent church. This paper begins by looking at some of the major strands in the religious thinking of Pearse, before going on to concentrate on the people and ideas which influenced Chilembwe both in Nyasaland and the United States. It argues that while many of these ideas were initially influenced by radical evangelical thought in the area of racial injustice, Chilembwe's thinking in the months immediately preceding his rebellion became increasingly obsessed by the possibility that the End Time prophecies of the Book of Daniel might apply to the current political position in Nyasaland. The conclusion is that much more academic attention needs to be given to the millennial aspects of Chilembwe's thinking as a contributory motivation for rebellion.

DEVELOPMENT TRENDS AND PROSPECTS OF ECONOMIC AND TRADE COOPERATION BETWEEN CHINA AND UKRAINE

2018 ◽  
Vol 2018 (6) ◽  
pp. 3-12
Author(s):  
Zhang DONGYANG ◽  
Keyword(s):  
Free Trade ◽  
Bilateral Trade ◽  
The United States ◽  
Economic Cooperation ◽  
Free Trade Zone ◽  
Asia Pacific ◽  
Economic Downturn ◽  
The European Union ◽  
Association Agreement ◽  
The Eu

The status and prospects of development of trade and economic relations between Ukraine and China are considered. It is proved that bilateral cooperation in the trade and economic sphere has made significant progress. In 2012–2017, China was the second largest trading partner of Ukraine after Russia. However, the problem of imbalance in imports and exports between Ukraine and China has not yet been resolved. In addition, the scale and number of projects in which Ukraine attracts Chinese investment is much less than investments from European countries and the United States. It is justified that trade and economic cooperation between Ukraine and China is at a new historical stage. On the one hand, Ukraine signed the Association Agreement with the European Union, and on January 1, 2016, the rules of the free trade zone between Ukraine and the EU entered into force. This helps to accelerate the integration of Ukrainian economy into European one. On the other hand, the global economic downturn requires the introduction of innovations in the model of cooperation. The Chinese initiative “One belt is one way” is one of the variants of the innovation model of cooperation. Its significance is to unite the Asia-Pacific region with the EU in order to join the Eurasian Economic Union, create a new space and opportunities for development and achieve prosperity with the Eurasian countries. All this forms unprecedented opportunities for development of bilateral economic and trade relations. It seems that to fully open the potential of Ukrainian economy and expand bilateral trade and economic cooperation, it is necessary to take into account such proposals as the establishment of the Sino-Ukrainian industrial park, the promotion of cooperation in the field of electronic commerce, the formation of the Sino-Ukrainian free trade zone and enhanced interaction within multilateral mechanisms (for example, the Shanghai Cooperation Organization and the interaction of China and the countries of Central and Eastern Europe in the 16 + 1 format).

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