Socialbots supporting human rights

TL;DR

This study investigates the role of socialbots in Mexican Twitter during a human rights report, showing they can support information spread and suggesting bot taxonomies should include non-adversarial roles.

Contribution

It adapts and applies bot detection and sentiment analysis techniques to Spanish tweets, revealing non-adversarial roles of socialbots in information dissemination.

Findings

Bots aided in information proliferation among humans

Proposed adaptations improve Spanish bot detection

Techniques applicable to other non-English social media data

Abstract

Socialbots, or non-human/algorithmic social media users, have recently been documented as competing for information dissemination and disruption on online social networks. Here we investigate the influence of socialbots in Mexican Twitter in regards to the "Tanhuato" human rights abuse report. We analyze the applicability of the BotOrNot API to generalize from English to Spanish tweets and propose adaptations for Spanish-speaking bot detection. We then use text and sentiment analysis to compare the differences between bot and human tweets. Our analysis shows that bots actually aided in information proliferation among human users. This suggests that taxonomies classifying bots should include non-adversarial roles as well. Our study contributes to the understanding of different behaviors and intentions of automated accounts observed in empirical online social network data. Since this type of analysis is seldom performed in languages different from English, the proposed techniques we employ here are also useful for other non-English corpora.