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Collegial Competition at the Cornerstone Contest

Posted: May, 12, 2015

By: Susan Ayasse Gr...

The career evening and datathon with Cornerstone was a huge hit.  

On the evening of April 30th, several staff from Cornerstone came to D-Lab to talk about work as an economic consultant: a practical application of rigorous quantitative research and analysis.  The culture at Cornerstone - a mixture of rigor and collegiality, of suits and jeans, of financial district and tech industry - is a great fit for D-Lab!

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Training Social Scientists for the Internet of Things #DataEDGE

Posted: May, 08, 2015

By: Sebastian P Benthall

At the DataEDGE conference today, Quentin Hardy interviewed Michael Chui, senior fellow of the McKinsey Global Institute, about the Internet of Things (IoT). Representing a management consulting firm, Chui emphasized the business potential of IoT. He maintains that this sector hold great promise.

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Causality in complex networks

Posted: Apr, 22, 2015

By: Sebastian P Benthall

One of the opportunities and challenges of 'data science' is that it allows you to bring the methodological flexibility of scientific computing to bear on newly available, complex data sets from ubiquitous sensors and the Web. This is an opportunity because it means there are ways we can confirm old theories using ecologically valid observational data, as well as potentially prove new theories. It is a challenge because ecological data does not isolate the factors of interest and the techniques for deriving causal conclusions from it are notoriously tricky and often statistically weak.

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Cornerstone Research – Career Evening and Economic Consulting Datathon, April 30 and May 2

Posted: Apr, 22, 2015

By: Susan Ayasse Gr...

Introducing the Cornerstone Research Economic Consulting Datathon

Cornerstone Research, in partnership with D-Lab, is excited to announce the first-ever Economic Consulting Datathon: an opportunity for UC Berkeley students to showcase their programming skills, their expertise in statistical and econometric techniques, and their economic acumen.

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Address Geocoding: options for the UC Berkeley Community

Posted: Apr, 16, 2015

By: Patty Frontiera

Introduction

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Introducing Social Computing

Posted: Feb, 09, 2015

By: Sebastian P Benthall

A perennial challenge for the D-Lab is how to target our trainings. We are aware of a great unmet need for training social scientists, especially graduate students, in learning basic technical skills. We are always looking for ways to make our trainings more accessible and inclusive.

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Scraping New York Times Articles with Python: A Tutorial

Posted: Feb, 03, 2015

By: Rochelle

This tutorial demonstrates how to use the New York Times Articles Search API using Python. From the API's documentation:

With the Article Search API, you can search New York Times articles from Sept. 18, 1851 to today, retrieving headlines, abstracts, lead paragraphs, links to associated multimedia and other article metadata. 

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D-Lab is hiring grad students to join us this Spring

Posted: Nov, 06, 2014

By: Patty Frontiera

We're looking for grad students to join us in the D-Lab this Spring.

If you feel inspired to help fellow researchers and students learn about and work with data analysis methods and tools, we're interested in hiring you.  We are the Social Sciences Data Laboratory (D-Lab). We have an open, inclusive culture that values diversity and open exchange. We'll let you develop leadership in a particular area while working collaboratively with other students and staff.  Our needs tend to fall into three categories, described below.

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D-Lab is Hiring Undergraduate Interns

Posted: Aug, 06, 2014

By: Katy R Pool

D-Lab is hiring Undergraduate Interns!

We will need availability between the hours of 9am-5pm M-F with a maximum of 16-20 hours per week. Junior or Senior Undergraduates. 

Please see the minimum qualifications below: 

DESKTOP SUPPORT

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Human Rights Coverage Over Time: A Tutorial in Automated Text Analysis

Posted: Jun, 30, 2014

By: Rochelle

I’ve learned a lot through the D-Lab, from Python and basic coding to automated text analysis and web scraping. In the spirit of paying it forward, this blog post provides a tutorial on one specific project that I was able to perform using the skills I gained at the D-Lab: analyzing human rights media coverage. What determines American media coverage on human rights? How does it vary over time and space? What characterizes it substantively?

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