Matching Items (2)
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- All Subjects: Income
- All Subjects: Census
- Creators: Chen, Vivian Young
Description
Over 2 billion people are using online social network services, such as Facebook, Twitter, Google+, LinkedIn, and Pinterest. Users update their status, post their photos, share their information, and chat with others in these social network sites every day; however, not everyone shares the same amount of information. This thesis explores methods of linking publicly available data sources as a means of extrapolating missing information of Facebook. An application named "Visual Friends Income Map" has been created on Facebook to collect social network data and explore geodemographic properties to link publicly available data, such as the US census data. Multiple predictors are implemented to link data sets and extrapolate missing information from Facebook with accurate predictions. The location based predictor matches Facebook users' locations with census data at the city level for income and demographic predictions. Age and relationship based predictors are created to improve the accuracy of the proposed location based predictor utilizing social network link information. In the case where a user does not share any location information on their Facebook profile, a kernel density estimation location predictor is created. This predictor utilizes publicly available telephone record information of all people with the same surname of this user in the US to create a likelihood distribution of the user's location. This is combined with the user's IP level information in order to narrow the probability estimation down to a local regional constraint.
ContributorsMao, Jingxian (Author) / Maciejewski, Ross (Thesis advisor) / Farin, Gerald (Committee member) / Wang, Yalin (Committee member) / Arizona State University (Publisher)
Created2012
Description
Over the years from 2009 to 2017, the people of Arizona witnessed the state consistently defunding the schools, its students academically underperforming, and as a result, the poverty achievement gap widening. Even with the efforts in recent years to re-invest in education, Arizona’s education funding falls below its level at 2008 and the national average. Among Arizona’s funding sources is the Public School Tax Credit, a unique legislation for the state that allows for taxpayers to donate money to certain programs at Arizona public schools and reduce their state income tax liability dollar-for-dollar. Because of the already severe achievement gap in Arizona, this funding source which relies on surrounding neighborhoods’ income raises the concern that, instead of helping Arizona students, it is exacerbating the existing achievement gap. The purpose of this paper is to examine the relationship between income and donations received by schools to determine the validity of this concern. To ensure a comprehensive examination of the relationship between income and donations received, regression tests are run on both the aggregate level and individual level. The tests find that, although income does have a statistically significant correlation with the donations received, it is only positive for the effect of total income on total donations, negative for the effect of average income per return on average donation per donor, and negative for average income per return on total donations. The results imply that to garner high donations, it matters less to be located in a high-earning neighborhood and more important to be located in a moderate-earning neighborhood with a lot of people donating using this credit. Therefore, the concern of income’s effect on donations is valid, but perhaps not in the straightforward way that we would expect.
ContributorsChen, Vivian Young (Author) / Kenchington, David (Thesis director) / Brown, Jenny (Committee member) / Department of Finance (Contributor) / School of Accountancy (Contributor) / School of Politics and Global Studies (Contributor) / Barrett, The Honors College (Contributor)
Created2020-12