Linguistic and News-Sharing Polarization During the 2019 South American Protests.

In computational social science, two parallel research directions exploring – news consumption patterns and linguistic regularities – have made significant inroads into better understanding complex political polarization in the era of ubiquitous internet. However, little or no literature exists that presented a unified treatment combining both these research directions. When working on social events from countries that do not speak English as a first language, computational linguistic resource availability is often a barrier to sophisticated linguistic analyses. In this work, we analyze an important sociopolitical event, the 2019 South American protests, and demonstrate that (1) a combined treatment offers a more comprehensive understanding of the event; and (2) these cross-cutting methods can be applied in a synergistic way. The insights gained by the combination of these methods include that polarization in users’ news sharing patterns was consistent with their stances towards the government and that polarization in their language mainly manifested along ideological, political, or protest-related lines. In addition, we release a massive dataset of 15 million tweets relevant to this crisis.