This two-part workshop series will prepare participants to move forward with research that uses text analysis, with a special focus on humanities and social science applications.
I'm a second year MIMS Student with a focus on Data Science and Natural Language Processing. During the Summer 2023, I interned at Genentech as a Data Science Intern.
Daniel Lobo is a PhD student in the Department of Sociology with an emphasis in Political Economy at UC Berkeley. He is broadly interested in how culture, or the unspoken “rules of the game,” reproduces inequality within a system of racial capitalism. At the individual level, he is interested in documenting and measuring the extent to which cultural capital and social capital enable or constrain opportunities for intergenerational mobility. At the organizational level, he is interested in documenting and measuring the extent to which culturally-based selection and promotion processes...
This two-part workshop series will prepare participants to move forward with research that uses text analysis, with a special focus on humanities and social science applications.
How can we use neural networks to create meaningful representations of words? The bag-of-words is limited in its ability to characterize text, because it does not utilize word context.
This two-part workshop series will prepare participants to move forward with research that uses text analysis, with a special focus on humanities and social science applications.
I’m a D-Lab GSR and a graduate student in The Goldman School’s Master of Public Policy/The I School’s Graduate Certificate in Applied Data Science. I have 5 years of experience working on data problems in government and nonprofits. I’m interested in social policy, program evaluation, and computational methods. Python is my principal language, but I’ve developed experience using and teaching a variety of other tools, including R, Excel, Tableau, and JavaScript. I deeply enjoy teaching data science methods and am excited to be a part of the D-Lab.
Former D-Lab Postdoc and Senior Data Science Fellow
Berkeley Law
Aniket Kesari was a postdoc and data science fellow at D-Lab. He is currently a research fellow at NYU’s Information Law Institute, and will join the faculty of Fordham Law School in 2023. His research focuses on law and data science, with particular interests in privacy, cybersecurity, and consumer protection.
How can we use neural networks to create meaningful representations of words? The bag-of-words is limited in its ability to characterize text, because it does not utilize word context.