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Mareike Lisker

Publications and source records attributed to Mareike Lisker.

4 recordsLinked to original sources

Who's Behind It? Annotating and Extracting Conspiratorial Actors from German Telegram Posts

Conspiracy theories commonly attribute important events to the actions of powerful and secretive actors. While computational research has largely focused on document-level analyses of conspiracy theories, less attention has been paid to identifying the actors that drive such narratives. We develop annotation guidelines for conspiratorial actors, present a span-annotated corpus of German Telegram posts, and investigate their automatic extraction using transformer-based models. We further apply the resulting model to the \textit{Schwurbelarchiv}, a large-scale archive of German conspiracy-related Telegram channels. Our results demonstrate that conspiratorial actors can be annotated with meaningful agreement and extracted with reasonable accuracy despite the linguistic complexity of conspiracy discourse, enabling large-scale analyses of actor representations in conspiracy narratives.

cs.CL

Bye Bye Perspective API: Lessons for Building and Governing Measurement Infrastructure

Perspective API closes at the end of 2026, removing the de facto standard for toxicity measurement and exposing researchers' dependence on a tool they did not control. Drawing on this case, we argue that a research field must build and govern its own measurement infrastructure rather than borrow it. Surveying 241 papers that use or study Perspective, we show what depending on it cost the research community: claims reaching past what the tool could support, results that shifted when its model was silently retrained, and disparities researchers could measure but not explain. These failures were amplified throughout the LLM lifecycle, where Perspective supplied the labels, filtered the corpora, and graded the systems trained on each, rewarding errors rather than catching them. To keep the instrument open to study after shutdown, we release Perspective scores for 5.9 million text snippets from 77 datasets. We further specify ten requirements for measurement infrastructure a field owns, and argue that what blocks such infrastructure is not technical capability but the value the field places on infrastructure work.

cs.CL

Debunking with Dialogue? Exploring AI-Generated Counterspeech to Challenge Conspiracy Theories

Counterspeech is a key strategy against harmful online content, but scaling expert-driven efforts is challenging. Large Language Models (LLMs) present a potential solution, though their use in countering conspiracy theories is under-researched. Unlike for hate speech, no datasets exist that pair conspiracy theory comments with expert-crafted counterspeech. We address this gap by evaluating the ability of GPT-4o, Llama 3, and Mistral to effectively apply counterspeech strategies derived from psychological research provided through structured prompts. Our results show that the models often generate generic, repetitive, or superficial results. Additionally, they over-acknowledge fear and frequently hallucinate facts, sources, or figures, making their prompt-based use in practical applications problematic.

cs.CL

Data Ethics in the Fediverse: Analyzing the Role of Instance Policies in Mastodon Research

This article addresses the disconnect between the individual policy documents of Mastodon instances--many of which explicitly prohibit data collection for research purposes--and the actual data handling practices observed in academic research involving Mastodon. We present a systematic analysis of 29 works that used Mastodon as a data source, revealing limited adherence to instance--level policies despite researchers' general awareness of their existence. Our findings underscore the need for broader discussion about ethical obligations in research on alternative, decentralized social media platforms.

cs.SI