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Assessing the Impact of Online Personalization on Algorithmic Culture

Today, many major websites personalize the content that they show to users. Examples include: Google Search, which personalizes search results to try and surface more relevant content; Amazon and Netflix, which personalize product and movie recommendations; and Facebook, which personalizes each user’s news-feed to highlight engaging content. The proliferation of personalization on the Web is driven by the explosion of Big Data that is available about people’s online and offline behavior.

Although there are cases where personalization is beneficial to users, scientists and regulators have become increasingly concerned that personalization may also harm Web users. For example, sociologists and political scientists are concerned that online Filter Bubbles may create “echo chambers” that increase political polarization. Similarly, personalization on e-commerce sites can be used to implement price discrimination.

Given the enormous number of people who rely on the Web, it is imperative that we understand how personalization algorithms are being deployed, and the effect that they have on Web users. The Personalization Research group at Northeastern (which includes David Lazer, Alan Mislove, and Christo Wilson) is currently undertaking several studies aimed at disentangling these issues, including looking at personalization on search engines, as well as price discrimination and price steering on e-commerce sites.

The project team consists of David Lazer, Alan Mislove, Christo Wilson, Aniko Hannak, Ronald Robertson, and Piotr Sapieżyński. More information about personalization, filter bubble, and algorithmic culture research at Northeastern can be found on the group’s homepage:

Publications and Presentations

Chen, Le and Christo Wilson. “Observing Algorithmic Marketplaces In-the-Wild.” ACM SIGecom Exchanges, 15(2). pp 34-39. 2017.

Epstein, Ronald Robertson, David Lazer, and Christo Wilson. “Suppressing the Search Engine Manipulation Effect (SEME).” Proceedings of the ACM: Human-Computer Interaction, 1(2). 2017.

Hannak, Aniko, Claudia Wagner, David Garcia, Alan Mislove, Markus Strohmaier, and Christo Wilson. “Bias in Online Freelance Marketplaces: Evidence from TaskRabbit and Fiverr.” Proceedings of the 20th ACM Conference on Computer-Supported Cooperative Work and Social Computing. Portland, Oregon. 2017.

Sapiezynski, Piotr, Valentin Kassarnig, Christo Wilson, Sune Lehmann, and Alan Mislove. “Academic Performance Prediction in a Gender-Imbalanced Environment.” Proceedings of the FATREC Workshop on Responsible Recommendation. Como, Italy. 2017.

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