Learning about Machine Learning: An Extended Assignment to Classify Twitter Accounts

We describe a four-week series of assignments in an undergraduate AI course at a liberal arts college developing a supervised learning solution to the problem of classifying Twitter accounts as either a person account or a non-person account (e.g. organization or spambot). This problem employs real data in an ongoing research project by the first author, yet is accessible to students with limited programming expertise. The students were able to experience a complete cycle of creating a machine learning solution: exploring raw data, creating a training set, engineering features, comparing different classifiers, evaluating the results, and performing error analysis. We received positive feedback from the students and intend to refine the assignment and make it available (together with the created training data) for use by the research community.