Nick Vincent

PhD student in the People, Space, and Algorithms Research Group led by Dr. Brent Hecht

Research interests: human-computer interaction, human-centered machine learning, social computing, and computational social science.

Technology and Social Behavior Ph.D. program

(joint program in Computer Science and Communication)

Northwestern University

Evanston, Illinois

My research focuses on studying the relationships between human-generated data and computing technologies to mitigate negative impacts of these technologies. I am especially interested in research that (1) makes people aware of the value of their data and (2) helps people leverage the value of their data. My work relates to concepts such as "data dignity", "data as labor", "data leverage", and "data dividends".

Should you prefer a more classic computer science personal website experience, append "/static/nojs.html" to your URL or click this link.

News Coverage

  1. Data dividends in Bloomberg.

    Peter Coy, "Facebook and Others Should Pay Us for Our Data. Here’s One Way.", May 2021.

  2. Data leverage in the MIT Technology Review.

    Karen Hao, "How to poison the data that Big Tech uses to surveil you", March 2021.

  3. Data leverage in Fortune.

    Jonathan Vanian and Jeremy Kahn, "Your data is a weapon that can help change corporate behavior", February 2021. This also appeared in the ACM TechNews.

  4. Data strikes in Quartz.

    Nicolás Rivero, "Is it time for Netflix subscribers to go on strike?", July 2020.

  5. Value of Wikipedia in the New York Times.

    John Herrman, "YouTube May Add to the Burdens of Humble Wikipedia", March 2018. This was also covered on the Northwestern Computer Science website.

Blog Posts

  1. Work in progress Observable post: Powerful Technologies and Their Power Laws: Estimating Machine Learning Systems' Data Leverage Vulnerabilities. Last Updated April 2021.
  2. Why You’re an Expert "Language Model Trainer"! March 2021.
  3. Don’t give OpenAI all the credit for GPT-3: You might have helped create the latest “astonishing” advance in AI too. September 2020.
  4. "Data Strikes": A New Form of Leverage for Tech Users? Guest post on the Data Dividend Project blog. September 2020.

Multimedia

  1. (Podcast) On Data Dividends - RadicalxChange Podcast. With Yakov Feygin and Matt Prewitt, May 2021.
  2. (Video) Data Agency: Individual or Shared? With Matt Prewitt, Kaliya Young, and Jennifer Lyn Morone, Jan 2021.
  3. (Video) Data Driven Economy for All - 2020 RxC Conference. With Hanlin Li, Yakov Feygin, and Brent Hecht. July 2020.

Peer-reviewed Publications

  1. [ICWSM 2021]

    Chowdhury, F.A., Liu, Y., Saha, K., Vincent, N. , Neves, L., Shah, N., and Bos, M.W.

    CEAM: The Effectiveness of Cyclic and Ephemeral Attention Models of User Behavior on Social Platforms. To Appear in Proceedings of the 15th International AAAI Conference on Web and Social Media (ICWSM) .

  2. [CSCW 2021]

    Vincent. N. and Hecht, B. 2021.

    A Deeper Investigation of the Importance of Wikipedia Links to Search Engine Results To Appear in CSCW 2021 / PACM Computer-Supported Cooperative Work and Social Computing.

  3. [CSCW 2021]

    Vincent. N. and Hecht, B. 2021.

    Can “Conscious Data Contribution” Help Users to Exert “Data Leverage” Against Technology Companies? To Appear in CSCW 2021 / PACM Computer-Supported Cooperative Work and Social Computing.

  4. [CHI 2021]

    Saha, K., Liu, Y., Vincent, N. , Chowdhury, F.A., Neves, L., Shah, N., and Bos, M. 2021.

    AdverTiming Matters: Examining User Ad Consumption for Effective Ad Allocations on Social Media. Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems .

  5. [FAccT 2021]

    Vincent, N. , Li, H., Tilly, N., Chancellor, S., Hecht, B. 2021.

    Data Leverage: A Framework for Empowering the Public in its Relationship with Technology Companies. To appear in Proceedings of the 2021 Conference on Fairness, Accountability, and Transparency.

  6. [CSCW 2019]

    Li, H. *, Vincent, N. *, Tsai, J., Kaye, J., and Hecht, B. 2019.

    How Do People Change Their Technology Use in Protest?: Understanding “Protest Users”. CSCW 2019 / PACM Computer-Supported Cooperative Work and Social Computing. * indicates equal contributions.

  7. [ICWSM 2019]

    Vincent, N., Johnson, I., Sheehan, P., and Hecht, B. 2019.

    Measuring the Importance of User-Generated Content to Search Engines. AAAI ICWSM 2019 .

  8. [The Web Conference 2019]

    Vincent, N., Hecht, B., and Sen, S. 2019.

    “Data Strikes”: Evaluating the Effectiveness of New Forms of Collective Action Against Technology Platforms. The Web Conference 2019 .

    Link to ACM Digital Library (includes PDF and HTML versions) | Link to PDF Preprint | Link to Archived code
  9. [CSCW 2018]

    Foong, E., Vincent, N., Hecht, B., and Gerber, E. 2018.

    Women (Still) Ask For Less: Gender Differences in Wage-Setting and Occupation in an Online Labor Marketplace. CSCW 2018 / PACM Computer-Supported Cooperative Work and Social Computing .

  10. [CHI 2018]

    Vincent, N., Johnson, I., and Hecht, B. 2018.

    Examining Wikipedia with a Broader Lens: Quantifying the Value of Wikipedia's Relationships with Other Large-Scale Online Communities. ACM CHI 2018.

    * Best paper award (top 1% of submissions)

Workshop Papers and Other Preprints

  1. [Collective Intelligence 2020 (non-archival) ]

    Vincent, N. and Hecht, B. 2020.

    Can “Conscious Data Contribution” Help Users to Exert “Data Leverage” Against Technology Companies? ACM Collective Intelligence 2020.

  2. [WikiWorkshop 2020 (non-archival) ]

    Vincent, N. and Hecht, B. 2020.

    A Deeper Investigation of the Importance of Wikipedia Links to the Success of Search Engines. WikiWorkshop 2020.

  3. [arXiv Preprint]

    Vincent, N., Li, Y., Zha, R. and Hecht, B., 2019.

    Mapping the Potential and Pitfalls of" Data Dividends" as a Means of Sharing the Profits of Artificial Intelligence. arXiv preprint arXiv:1912.00757.

    Link to arXiv page
  4. [BIBM 2015 Workshop on Biomedical Visual Search and Deep Learning]

    Stier, N., Vincent, N. , Liebeskind, D. and Scalzo, F. 2015.

    Deep learning of tissue fate features in acute ischemic stroke. Bioinformatics and Biomedicine (BIBM) 2015.

  5. [BIBM 2015 Workshop on Biomedical Visual Search and Deep Learning]

    Vincent, N., Stier, N., Yu, S., Liebeskind, D.S., Wang, D.J. and Scalzo, F. 2015.

    Detection of hyperperfusion on arterial spin labeling using deep learning. Bioinformatics and Biomedicine (BIBM) 2015.