Extracted a large dataset of issues from several GitHub projects and built statistical models (zero inflated negative binomial regression and a linear mixed-effects model) to quantify coordination costs and evaluate the factors associated with it. (paper under review)

The goal of this project is to predict labels assigned to issues on Github. Both text and social features were used in a Stacked classifier in Weka (also modified its source code). [Report]

Many of us have participated for social causes online often by sharing Facebook posts / Tweets. However, there is no easy way for someone to show the causes she has contributed for in the past. This project aims to build a web application where users can maintain a profile of their online social activism (often called slactivism). Theories from social psychology have shown that people perform desirable actions if they know those actions have had a positive impact in the past. Therefore, an important outcome of our application would be to increase user's motivation to participate in online social activism. The application was developed using the Meteor framework and written entirely in Javascript and HTML / CSS. This was a team project and my role was the conceptualization of the idea, mining and displaying relevant Tweets automatically, and authentication using an OAuth based Facebook login.[Source] [Demo]

Recently, Github has emerged as a useful platform to allow people to collaborate on government projects both in building software and creating policies. Since Github also provides a rich set of social media features, these interactions create a complex network that provides insightful information on the way users collaborate. Our primary hypothesis, informed from theory is to evaluate if members within an organization have more ties or not. We then build on this finding to better understand various aspects of collaboration such as reciprocity and homophily. [Report]

Edit wars are conflicts among editors of Wikipedia, when editors repeatedly overwrite each other’s content. The goal of this project is to create an agent-based model of edit wars in order to study the influence of various factors involved in consensus formation. We model the behavior of agents using theories of group stability and reinforcement learning.[Paper]

The proximity of edits in time and space(e.g. same paragraph, line, etc.) can be measured to understand the level of concurrent modifications in a Wikipedia article. The effects of such concurrency measures on a set of randomly chosen 'good' and 'featured' class articles were studied. [Report]

Hackathons are becoming increasingly common not only in industry but also in academia and government. The primary goal of hackathons is bring together a group of individuals in a face-to-face setting that typically last a few days and involve intense software development events. However, there are several challenges involved in organizing hackathons such as selecting the right mix of participants, determining its duration and setting a set of expected outcomes. In this project, we aim to build models and tools to facilitate organizers in designing and evaluating hackathons.