Oh wait, PhD in what? I leverage maths, computer science and data science to help understanding and tackling social challenges. My main research focus is on collective intelligence in decentralized decision-making and inforfmation disorders. In more details, I model various voting schemes to derive theoretical insights on those. I further work on experimenting with the new voting paradigms, confronting and enriching mathematical results with real-world observations. I also studied the credibility crisis of traditional media as news migrated to the web.
As of August 2022, I am also a Democracy Doctoral Fellow at the Ash Center at the Havrard Kennedy School. I hope that connecting fields such as political philosophy and mathematics may spur creative research and result in complementary perspectives through which we can better understand the world -- and uncover ways to incrementally improve governance systems.
I love playing basketball, running and windsurfing. The basketball community brought me more than I could tell, and I wanted to give back launching the BeeGames association in 2015 to foster cross-functional collaboration between companies, universities, and basketball professionals. Recruiters, former professional athletes and students met on court, in the adversity of a basketball game.
Also, growing up, I fantasized becoming a journalist. Over summers, I conducted local reportages on books fairs, fireworks, concerts... and hosted the 2012 Olypmpics chronicle for a local radio, Soleil de Re. I also launched an interview program on the webradio Radio Parentheses, where I asked scientists and politicians to share their perspectives with highschoolers. As I moved to the other side of the Atlantic, I told stories about my discovery of the US through my show Terre Américaine. I created my high school's newspaper in 2013, that has been tremedously improved by generations of students.
Liquid democracy is a decision-making process that was proposed in the 60s as an alternative to direct democracy and representative democracy. It relies on letting agents choose between voting themselves and transitively delegating their votes to better-informed agents in their neighbourhood. The agents that receive votes make a decision through a weighted majority, where a person's weight equals the number of person she represents after delegation. While liquid democracy has been seen as a system that could combine the best aspects of direct and representative democracies, it could also result in concentration of powers in the hands of a few. In fact, real-world implementations of liquid democracy already did. In this work, we investigate conditions on the delegation mechanism and on the graph topology that would self-regulate the largest weight and induce situations where liquid democracy outperforms direct and representative democracies.
However small the Republic may be, the Representatives must be raised to a certain number, in order to guard against the cabals of a few; and however large it may be, they must be divided to certain number, in order to guard against the confusion of a multitude. (Federalist Paper No.10) James Madison
We analyze the optimal size of a congress in a representative democracy. We take an epistemic view where voters decide on a binary issue with one ground truth outcome, and each voter votes correctly according to their competence levels in [0, 1]. Assuming that we can sample the best experts to form an epistemic congress, we find that the optimal congress size should be linear in the population size. This result is striking because it holds even when allowing the top representatives to be accurate with arbitrarily high probabilities. We then analyze real world data, finding that the actual sizes of congresses are much smaller than the optimal size our theoretical results suggest. We conclude by analyzing under what conditions congresses of sub-optimal sizes would still outperform direct democracy, in which all voters vote.
This work relies on the assumption that there exists a better option, and that the point of democracy is to uncover it. This is a classical approach that has validity when studying the legislative process, in which expertise is required, but that does not model well all types of elections. Further, one could question whether the goal of democracy is to make correct decisions, or to produce outcomes deemed legitimate and representative. Finally, other desiderata (such as the cost of voting, the cost of maintaining a large congress...) are also at stake when considering the optmal number of representatives. Future work shall incorporate these philosophical and practical concerns in the next generation of mathematical models.
If you would like to lear more about the maths of democracy, have a look at Professor Procaccia's fantastic class, Optimized Democracy.
Revel, M., Lin, T., & Halpern, D. (2021). How Many Representatives Do We Need? The Optimal Size of an Epistemic Congress AAAI-22: Proc. of 36th AAAI Conference on Artificial Intelligence, 2022. Forthcoming.
Revel, M., Lin, T., & Halpern, D. (2021). How Many Representatives Do We Need? The Optimal Size of an Epistemic Congress presented at the 2021 Conference on Web and Internet Economics (WINE) by Tao .
Native Ads and the Credibility of Online Publishers
The digitization of news publishing has resulted in new ways for advertisers to reach readers, including additional native advertising formats that blend in with news. However, native ads may redirect attention off-site and affect the readers' impression of the publishers. Using a combination of observations of ad content across many publishers and two large randomized experiments, we investigate the characteristics of a pervasive native ad format and compare the impact of different native ads characteristics on perceived news credibility. Analyzing 1.4 million collected ad headlines, we found that over 80% of these ad headlines use a clickbait-style and that politics is among the most common topics in ads. In two randomized experiments (combined n=9,807), we varied the style and content of native ads embedded in news articles and asked people to assess the articles’ credibility. Experiment 1 (n=4,767) suggested that different publishers were impacted differently by the ads and motivated the more detailed design of Experiment 2 (n=5,040). This latter experiment used hundreds of unique combinations of ads, articles, and publishers to study effects of clickbait and political ads. Findings from this pre-registered experiment provide evidence that clickbait and, to a lesser extent, political ads, substantially reduce readers' perception of the articles' credibility. This phenomenon is driven by the least well-known publishers and by readers' prior familiarity with those publishers. Importantly, we rule out large effects of non-clickbait ads, compared with no ads, on readers' attitudes. Many publishers using clickbait native ads may trade short-term revenues for audience trust.
Varieties of Resonance: The Subjective Interpretations and Utilizations of Media Output in France.
Joint work with Adrien Abecassis and Bo Yun Park
The resonance of media output plays an important role in the age of misinformation and fake news. While scholars have extensively studied resonance, they have mostly focused on whether and why particular messages align with the predispositions of their intended audience rather than systematically analyzing how they are interpreted by the wider population. Based on a computational text analysis of the media output from more than a hundred different outlets in France and weekly surveys of what people have retained from the news during the same period, this paper investigates the ways in which media coverage trigger different types of resonance in accordance with people’s diverse interpretations and utilizations of the messages to which they have been exposed. We theoretically argue that resonance is not just an objective alignment between a message and one’s predispositions, but also a subjective interpretation and utilization of the message heard. We empirically identify three different types of subjective resonance: one used for problem-solving, one that is problem-aggravating, and another one that is problem-generating. This research contributes to a better understanding of the mechanisms of resonance by expanding on previous works on the cognitive, emotional, and interactional dimensions of resonance.
Alternative Realities in Troubled Democracies
I also moderated a panel and wrote an article for the general public about misinformation!
Learn about Tinnitus from Social Media
Joint work with Ryan Boyd, Aniruddha Deshpande, Alain Londero, Vinaya Manchaiah, Guillaume Palacios and Pierre Ratinaud
Individuals with tinnitus are highly heterogeneous in terms of etiology, the manifestation of symptoms, and the way they manage their condition. Most of these patients are likely to seek hearing health information and social support online via various websites or social media platforms. Indeed, information is easily accessible online. Further, in absence of evidence-based tinnitus care, patients with similar symptoms can regroup, share experiences, and exchange tips. Even after consultation with healthcare providers, some of the patients continue seeking information online when they feel they did not get satisfying information about treatment options and/or about their prognosis. The present study was aimed at examining the discussions around tinnitus in Reddit posts from 12,000 users over 8 years, using various Natural Language Processing (NLP) techniques. We examined the free-texts posts to understand the types of conversation about tinnitus in an online forum and the way in which people with tinnitus reach out to other people for support (informational, emotional, etc.) when coping with their conditions. We hope that this can provide insights, complementary to those collected in the clinical environment, to reflect on new ways to support tinnitus patients.
Manchaiah, V., Londero, A., Deshpande, A. K., Revel, M., Palacios, G., Boyd, R. L., & Ratinaud, P. (2022). Online discussions about tinnitus: What can we learn from natural language processing of Reddit posts?. American Journal of Audiology, 1-10.
Data, Models and Decisions
Probability, Statistics, Algebra and Data Science Review
I created and teach a 15-hour seminar in algebra, probability, statistics, micro-economy and data science for the MIT Technology and Policy Masters Students .
January and August 2021