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Harvard Successfully Uses Data Mining in Immigration Studies


There is an enormous amount of data out there. This data explosion is the result of the availability of high-tech data collection tools and advanced database technology. Tremendous amounts of data are stored in databases, data repositories and information warehouses and other information. Data mining involves extracting knowledge from the data in these large data bases to discover interesting patterns.

One of the areas where data mining software is used extensively in immigration research. William R. Kerr, a professor at Harvard Business School and William F. Lincoln of the University of Michigan studied the impact of changes in annual H-1B admission levels from 1995 to 2008 to analyze whether the controversial program is helpful or hurtful to American workers. By mining relevant immigration data, the researchers found that native-born workers and immigrant workers generally complement each other rather than compete for the same job and that immigrants have small but positive impact on the employment of native born workers.

Kerr’s study also looked at whether immigration promoted innovation by looking at data on patent applications and grants through May 2009 at the United States Patent and Trademark Office. To get information on the inventors’ immigration status or ethnicities, they applied data mining and name matching techniques to infer the ethnicity of inventors at any given firm. This helped them determine, for instance, whether the innovation was made by a Chinese or Indian immigrant.

Another more recent study by the Institute of Immigration Research is based mining information from discussions pertaining to immigration on Twitter, with specific emphasis on comprehensive immigration reform. Since February 2013, the project collected nearly 3 million tweets containing the word “immigration”. Using two different data mining applications, the researchers analyzed the tweets to find out who is talking to whom, what they’re discussing, and how these conversations are changing over time.

They identified “clusters” of five major groups of influential tweeters and are tracking how, when, and why Twitter users change their mind about immigration by examining their relationship to these clusters over time.

Data mining to discover knowledge in databases has immense potential for all kinds of industries. Companies use these techniques to predict consumer demand patterns, understand consumer tastes and preferences, and much more. Healthcare providers mine data to improve patient services, and understand disease patterns and drug reactions.

Managing data and processing it to extract useful information requires the application of right tools and techniques. A professional data mining company equipped with advanced software and an expert team of analysts can help businesses extract useful information or patterns from data in large databases to improve their performance and productivity.

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MOS Team

Managed Outsource Solutions (MOS) is a leading BPO company committed to providing business process outsourcing solutions for a wide range of industries such as Medical, Legal, Information Technology and Online Media.