Differences in misinformation sharing can lead to politically asymmetric sanctions.

In response to intense pressure, technology companies have enacted policies to combat misinformation. The enforcement of these policies has, however, led to technology companies being regularly accused of political bias. We argue that differential sharing of misinformation by people identifying with different political groups could lead to political asymmetries in enforcement, even by unbiased policies.

Blocking of counter-partisan accounts drives political assortment on Twitter.

There is strong political assortment of Americans on social media networks. This is typically attributed to preferential tie formation (i.e.

Shaping opinions in social networks with shadow banning.

The proliferation of harmful content and misinformation on social networks necessitates content moderation policies to maintain platform health. One such policy is shadow banning, which limits content visibility. The danger of shadow banning is that it can be misused by social media platforms to manipulate opinions.

Social media engagement and cryptocurrency performance.

Cryptocurrencies are highly speculative assets with large price volatility. If one could forecast their behavior, this would make them more attractive to investors. In this work we study the problem of predicting the future performance of cryptocurrencies using social media data.

Bots, disinformation, and the first impeachment of U.S. President Donald Trump.

Automated social media accounts, known as bots, have been shown to spread disinformation and manipulate online discussions. We study the behavior of retweet bots on Twitter during the first impeachment of U.S.