Google Tech Talk June 7, 2012 Presented by Steven Skiena. ABSTRACT A discipline of computational social science is emerging, applying large-scale text/data analysis to central problems in the humanities and social sciences. Here we study the problem of algorithmically-constructing quantitative measures of historical reputation. Who is more historically significant: Beethoven or Elvis? Washington or Lincoln? Newton or Einstein? Larry or Sergey? By exploiting large-scale data from several sources, we have developed a factor analysis-based ranking method which measures the relative importance of all the people described in Wikipedia in a rigorous way. We have validated our measure against published rankings of historical figures, demonstrating that our rankings are generally better than those of human experts. Our measure gives us the power to rigorously investigate several previously difficult-to-formalize questions, such as: -- Are the right people in the history books? -- How well do halls of fame correctly identify the most significant individuals? -- Are men and women treated equally in Wikipedia? -- Where can you donate money to maximize your personal fame? In this talk, I will discuss our methodology for ranking historical figures, with assessment results and applications. Our rankings are available for inspection at http://www.whoisbigger.com.
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