Ranking algorithms are the information gatekeepers of the Internet era. We develop a stylized framework to study the effects of ranking algorithms on opinion dynamics. We consider rankings that depend on popularity and on personalization. We find that popularity driven rankings can enhance...

Are dominant online search engines monopolies enjoying low contest-ability, due to high barriers to entry, or innovative first-movers? This paper argues that dominant online search engines maintain their leadership through an “innovation feedback loop”: a process whereby increasing R&D...

The use of search engines has become almost as important as e-mail as a primary online activity. Arguably, search engines are among the most important gatekeepers in today's digitally networked environment. Thus, it does not come as a surprise that the evolution of search technology and the...

This paper provides a simple theoretical framework to evaluate the effect of key parameters of ranking algorithms, namely popularity and personalization parameters, on measures of platform engagement, misinformation and polarization. The results show that an increase in the weight assigned to...

Competition authorities all over the world worry that integration between search engines (mainly Google) and publishers could lead to abuses of dominant position. In particular, one concern is that of own-content bias, meaning that Google would bias its rankings in favor of the publishers it...

We analyze a search engine market from a law and economics perspective and incorporate the choice of quality improving innovations by a search engine platform in a two-sided model of internet search engine. In the proposed framework we, first, discuss the legal issues the search engine market...

This paper studies competition in data-driven markets, that is, markets where the cost of quality production is decreasing in the amount of machine-generated data about user preferences or characteristics, which is an inseparable byproduct of using services offered in such markets. This gives...

In this study the dynamics of online product ratings is modeled based on the data for 59 items from 20 product categories. We account not only for the context dependence of subsequent reviews on previously posted reviews, but also for product type (search product or experience product). We...