With an increasing amount of data on every aspect of our daily activities – from what we buy, to where we travel, to who we know, and beyond – we are able to measure human behavior with precision largely thought impossible just a decade ago, creating an unprecedented opportunity to address longstanding questions in the social sciences. Leveraging this sea of information requires both scalable computational tools, and understanding how the substantive scientific questions should drive the data analysis. Lying at the intersection of computer science, statistics and the social sciences, the emerging field of computational social science fills this role, using large-scale demographic, behavioral and network data to investigate human activity and relationships.
The MSR NYC computational social science group is widely recognized as a leading center of CSS research. Our approach is motivated by two longstanding difficulties for traditional social science: first, that simply gathering observational data on human activity (e.g., who says what to whom, with what effect) is extremely difficult at scale and over time; and second, that running experiments to manipulate the conditions under which these measurements are made (e.g., randomly assigning large sets of interacting people to treatment and control groups) is even more challenging and often impossible.
In the first category, we exploit digital data that is generated by existing platforms (e.g., email, web browsers, Twitter) to generate novel insights into individual and collective human behavior (e.g., virality of online content, causal impact of recommendations, TV show and ad effectiveness). In the second category, we design novel “virtual lab” experiments that allow for larger scale, longer time horizons, and greater complexity and realism than is possible in physical labs (e.g. team problem solving, dynamics of cooperation over many days). In addition to advancing the state of the science, our work also contributes to innovative new products and strategic capabilities at Microsoft.
Currently seeking a full time research assistant at Microsoft Research in New York, NY under the supervision of Duncan Watts and Dan Goldstein. Tasks include running virtual lab experiments, conducting surveys using third-party providers, obtaining, cleaning, and manipulating large-scale datasets from the web or other sources, performing statistical analyses, and designing/maintaining a website. The position is ideal for a recent graduate wishing to gain research experience prior to pursuing a Ph.D. in computational social science either in a computer science or social science program.
Please find more information about Research Assistant positions here.