Online harassment remains a prevalent problem for internet users. Its impact is made orders of magnitude worse when multiple harassers coordinate to conduct networked attacks. This paper presents an analysis of 231 threads in Kiwi Farms, a notorious online harassment community. We find that networked online harassment campaigns consists of three phases: target introduction, network decision, and network response. The first stage consists of the initial narrative elements, that are approved or not in stage two and expanded in stage three. Narrative building is a common element of all three stages. The network plays a key role in narrative building, adding elements to the narrative in at least 80 % of the threads, resulting in sustained harassment. This finding is central to our model of Continuous Narrative Escalation (CNE), that has two parts: (1) narrative continuation, the action of repeatedly adding new information to the existing narrative and (2) escalation, the aggravation of harassment that occurs as a consequence. In addition, we present insights from our analysis of 100 takedown requests threads, discussing received abuse reports. We find that these takedown requests are misused by the community and are used as elements to further fuel the narrative. We use our findings and framework to come up with a set of recommendations, that can inform harassment interventions and make online spaces safer.

Conspiracy theories are increasingly a subject of research interest as society grapples with their rapid growth in areas such as politics or public health. Previous work has established YouTube as one of the most popular sites for people to host and discuss different theories. In this paper, we present an analysis of monetization methods of conspiracy theorist YouTube creators and the types of advertisers potentially targeting this content. We collect 184,218 ad impressions from 6,347 unique advertisers found on conspiracy-focused channels and mainstream YouTube content. We classify the ads into business categories and compare their prevalence between conspiracy and mainstream content. We also identify common offsite monetization methods. In comparison with mainstream content, conspiracy videos had similar levels of ads from well-known brands, but an almost eleven times higher prevalence of likely predatory or deceptive ads. Additionally, we found that conspiracy channels were more than twice as likely as mainstream channels to use offsite monetization methods, and 53% of the demonetized channels we observed were linking to third-party sites for alternative monetization opportunities. Our results indicate that conspiracy theorists on YouTube had many potential avenues to generate revenue, and that predatory ads were more frequently served for conspiracy videos.