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Among the goals of information operations are to change the overallinformation environment vis-\'a-vis specific actors. For example, "trollingcampaigns" seek to undermine the credibility of specific public figures,leading others to distrust them and intimidating these figures into silence. Toaccomplish these aims, information operations frequently make use of "trolls"-- malicious online actors who target verbal abuse at these figures. In Brazil,in particular, allies of Brazil's current president have been accused ofoperating a "hate cabinet" -- a trolling operation that targets journalists whohave alleged corruption by this politician and other members of his regime.Leading approaches to detecting harmful speech, such as Google's PerspectiveAPI, seek to identify specific messages with harmful content. While thisapproach is helpful in identifying content to downrank, flag, or remove, it isknown to be brittle, and may miss attempts to introduce more subtle biases intothe discourse. Here, we aim to develop a measure that might be used to assesshow targeted information operations seek to change the overall valence, orappraisal, of specific actors. Preliminary results suggest known campaignstarget female journalists more so than male journalists, and that thesecampaigns may leave detectable traces in overall Twitter discourse.

Applying Word Embeddings to Measure Valence in Information Operations Targeting Journalists in Brazil