Eni Mustafaraj
Associate Professor of Computer Science
I love data, the Web, and web data. I aim to understand, critique, and transform web-based sociotechnical systems using data & web science.
I am a computational data scientist who studies the online information environment shaped by the interactions of algorithms, humans, and organizations. I typically focus on one web-based sociotechnical system at a time. I have studied Twitter, Google, Wikipedia, and YouTube. Since November 2023, I have turned my focus to TikTok. Students in my research lab, Wellesley Cred Lab, and in my 300-level course, CS 315 Data Science for the Web, are building tools to audit TikTok’s recommendation algorithm and study the flow of information in this platform.
I love collaborations! Since my arrival at Wellesley in 2008, I have had many long and rewarding research collaborations. During 2008-2014, I collaborated with Prof. Takis Metaxas, Samantha Finn ‘12 and a large number of Wellesley students in studying how rumors or other kinds of information spread in social networks like Twitter. From 2013-2017 I collaborated with Prof. Franklyn Turbak, Maja Svanberg ‘18, and Isabelle Li '20 on using data science and machine learning to understand how people learn to program in the MIT App Inventor online platform. Since 2015 I have been collaborating with Prof. Julie Walsh (Philosophy) on ways of integrating ethics of technology in our computer science and data science curriculum. Most recently, we received a grant from the NSF to support our work. As part of our project, we are co-teaching a cross-listed CS/PHIL course on Methods for Ethics of Technology and have started LEED (Laboratory on Ethics and Equity in Digital tech). Collaborating with other Wellesley faculty, I have co-founded the Data Science major; the Wellesley CAPS (Computational Analysis for Political Science) Lab with Prof. Maneesh Arora, and the Wellesley CHEL (Computational Housing Economics Lab) with Prof. Kyung Park.
I am particularly proud of the students of my research lab, the Wellesley Cred Lab. Many of the lab alums, with whom I have co-authored research papers while they were undergraduate students are excelling in graduate school, Emma Lurie ‘19, Khonzoda Umarova ‘20, Annabel Rothschild ‘20, Anna Kawakami ‘21, Junita Sirait ‘22. Mentoring undergraduate students is one of the main joys of my work at Wellesley and I have been fortunate to receive the NSF CAREER award to support this kind of research-focused teaching and mentoring.
Other courses I teach are CS111 Computer Programming and Problem Solving, one of the most fun and challenging intro courses at Wellesley, and two data science related courses: CS 234 Data, Analytics, and Visualization and CS 315 Data Science for the Web, in which my students work on real-world projects closely related to my research and learn how to use data science to make a social impact.
I love listening to podcasts and audiobooks. Some of my favorite living authors are Kazuo Ishiguro, Neal Stephenson, Rachel Cusk, and Elif Batuman. I like both speculative/science fiction (Ishiguro, Stephenson, etc.) and fictionalized memoirs (Cusk, Batuman, etc.).
Last updated on February 2024.
Education
- M.A. or M.S. or M.B.A., Polytechnic University of Tirana
- Ph.D., Philipps Universität Marburg
Current and upcoming courses
An introduction to problem-solving through computer programming. Students learn how to read, modify, design, debug, and test algorithms that solve problems. Programming concepts include control structures, data structures, abstraction, recursion, and modularity. Students explore these concepts in the context of interactive programs, data processing, and graphics or audio, using the Python programming language.
Students are required to attend an additional two-hour laboratory section each week.
[Registration as of Tuesday, September 3] This course is currently full and the Workday waitlist is closed. If a spot becomes available during the add period a student from the (now closed) waitlist will be contacted by course faculty and allowed to register by permission of instructor (POI). Students on the Fall 2024 waitlist will be given priority status for initial Spring 2025 registration; note that this priority does not guarantee a seat in the class.
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Data Science for the Web
CS315
In the past decade, we have experienced the rise of socio-technical systems used by millions of people: Google, Facebook, Twitter, Wikipedia, etc. Such systems are on the one hand computational systems, using sophisticated infrastructure and algorithms to organize huge amounts of data and text, but on the other hand social systems, because they cannot succeed without human participation. How are such systems built? What algorithms underlie their foundations? How does human behavior influence their operation and vice-versa? In this class, we will delve into answering these questions by means of: a) reading current research papers on the inner-workings of such systems; b) implementing algorithms that accomplish tasks such as web crawling, web search, random walks, learning to rank, text classification, topic modeling; and c) critically thinking about the unexamined embrace of techno-solutionism using a humanistic lens.. Enrollment in this course is by permission of the instructor only. Students who are interested in taking this course should fill out this Google Form. -
How do we educate the next generation of data scientists, software engineers, and user experience designers to think of their work as not just technical but also ethical? What moral responsibilities come with the design, adoption, use, and consumption of digital technology? The way that these questions are interrogated, discussed, and the sort of answers we might propose will be informed by a thoroughgoing interdisciplinary lens. Students will learn theoretical frameworks from both Philosophy and Computational and Data Sciences and work together to see how knowledge of frameworks from both disciplines serves to enrich our understanding of the ethical issues that face the development and employment of digital technologies, as well as empower us to find creative solutions. This course includes a sustained, semester-long research project, hence the additional meeting time.. Enrollment in this course is by permission of the instructor. Interested students should fill out this Google Form. (CS 299 and PHIL 222 are cross-listed courses.)