Human behaviour is thought to spread through face-to-face social networks, but it is difficult to identify social influence effects in observational studies9–13, and it is unknown whether online social networks operate in the same way14–19. Here we report results from a randomized controlled trial of political mobilization messages delivered to 61 million Facebook users during the 2010 US congressional elections. The results show that the messages directly influenced political self-expression, information seeking and real-world voting behaviour of millions of people. Furthermore, the messages not only influenced the users who received them but also the users’ friends, and friends of friends. The effect of social transmission on real-world voting was greater than the direct effect of the messages themselves, and nearly all the transmission occurred between ‘close friends’ who were more likely to have a face-to-face relationship. These results suggest that strong ties are instrumental for spreading both online and real-world behaviour in human social networks.

A ccording to indicators of political repression currently used by scholars, human rights practices have not improved over the past 35 years, despite the spread of human rights norms, better monitoring, and the increasing prevalence of electoral democracy. I argue that this empirical pattern is not an indication of stagnating human rights practices. Instead, it reflects a systematic change in the way monitors, like Amnesty International and the U.S. State Department, encounter and interpret information about abuses. The standard of accountability used to assess state behaviors becomes more stringent as monitors look harder for abuse, look in more places for abuse, and classify more acts as abuse. In this article, I present a new, theoretically informed measurement model, which generates unbiased estimates of repression using existing data. I then show that respect for human rights has improved over time and that the relationship between human rights respect and ratification of the UN Convention Against Torture is positive, which contradicts findings from existing research.Notes: Proportions closer to 1 indicate that the dynamic standard model outperforms the constant standard model at predicting the original repression variables. Proportions closer to 0 indicate the opposite. Proportions at 0.50 indicate that both models are predicting the items with about the same amount of error relative to each other. The dynamic standard model does a much better job of predicting the original repression variables, especially the event-based variables.

Some social connections are stronger than others. People have not only friends, but also best friends. Social scientists have long recognized this characteristic of social connections and researchers frequently use the term tie strength to refer to this concept. We used online interaction data (specifically, Facebook interactions) to successfully identify real-world strong ties. Ground truth was established by asking users themselves to name their closest friends in real life. We found the frequency of online interaction was diagnostic of strong ties, and interaction frequency was much more useful diagnostically than were attributes of the user or the user’s friends. More private communications (messages) were not necessarily more informative than public communications (comments, wall posts, and other interactions).

The science of human rights requires valid comparisons of repression levels across time and space. Though extensive data collection efforts have made such comparisons possible in principle, statistical measures based on simple additive scales made them rare in practice. This article uses a dynamic measurement model that contrasts with current approaches by (1) accounting for the fact that human rights indicators vary in the level of information they provide about the latent level of repression, (2) allowing realistic descriptions of measurement uncertainty in the form of credible intervals and (3) providing a theoretical motivation for modeling temporal dependence in human rights levels. It presents several techniques, which demonstrate that the dynamic ordinal item-response theory model outperforms its static counterpart.

To document human rights, monitoring organizations establish a standard of accountability, or a baseline set of expectations that states ought to meet in order to be considered respectful of human rights. If the standard of accountability has meaningfully changed, then the categorized variables from human rights documents will mask real improvements. Cingranelli and Filippov question whether the standard of accountability is changing and whether data on mass killings are part of the same underlying conceptual process of repression as other abuses. These claims are used to justify alternative models, showing no improvement in human rights. However, by focusing on the coding process, the authors misunderstand that the standard of accountability is about how monitoring organizations produce documents in the first place and not how academics use published documents to create data. Simulations and latent variables that model time in a substantively meaningful way validate the conclusion that human rights are improving.

The migration of political asylum seekers into the United States has long been a salient political topic; however, social scientists have yet to examine this process in its entirety and in the context of political changes since September 11, 2001. Previous research shows that humanitarian and strategic interests are important for decisions made by asylum officers but that research overlooks the decisions made by immigration judges. Here we examine decisions made by both asylum officers and immigration judges using data from a global set of countries, from 1999 to 2004. We find that the waning importance of human rights is more pronounced for asylum officers than for immigration judges after the attack on the World Trade Center. We also find that language heritage, specifically for asylum seekers from English-, Spanish-, and Arabic-speaking countries, substantially affects acceptance rates made by both decision-makers between the two time periods of our study.

This study explores the relationships between state violations of different human rights. Though most quantitative studies in international relations treat different types of repressive behaviors as either independent or arising from the same underlying process, significant insights are gained by conceptualizing different human rights violations as separate but dependent processes. We present a theoretical framework for conceptualizing the mechanisms relating human rights practices and produce a novel measurement strategy based on network analysis for exploring these relationships. We illustrate high levels of complementarity between most human rights practices. Substitution effects, in contrast, are occasionally substantial but relatively rare. Finally, using empirically informed Monte Carlo analyses, we present predictions regarding likely sequences of rights violations resulting in extreme violations of different physical integrity rights.

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