A Two-Phase Framework for Detecting Manipulation Campaigns in Social Media. - Dennis Assenmacher; Lena Clever; Janina Susanne Pohl; Heike Trautmann; Christian Grimme (HCI (14), 2020)

Deep Learning as a Competitive Feature-Free Approach for Automated Algorithm Selection on the Traveling Salesperson Problem. - Moritz Seiler; Janina Pohl; Jakob Bossek; Pascal Kerschke; Heike Trautmann (PPSN (1), 2020)

On the potential of normalized TSP features for automated algorithm selection. - Jonathan Heins; Jakob Bossek; Janina Pohl; Moritz Seiler; Heike Trautmann; Pascal Kerschke (FOGA, 2021)

Artificial Social Media Campaign Creation for Benchmarking and Challenging Detection Approaches. - Janina Susanne Pohl; Dennis Assenmacher; Moritz Vinzent Seiler; Heike Trautmann; Christian Grimme (ICWSM Workshops, 2022)

New Automation for Social Bots: From Trivial Behavior to AI-Powered Communication. - Christian Grimme; Janina Pohl; Stefano Cresci; Ralf Lüling; Mike Preuss (MISDOOM, 2022)

Immunize the Public against Disinformation Campaigns: Developing a Framework for Analyzing the Macrosocial Effects of Prebunking Interventions. - Johanna Klapproth; Saïd Unger; Janina Pohl; Svenja Boberg; Christian Grimme; Thorsten Quandt (HICSS, 2023)

Invasion@Ukraine: Providing and Describing a Twitter Streaming Dataset That Captures the Outbreak of War between Russia and Ukraine in 2022. - Janina Susanne Pohl; Simon Markmann; Dennis Assenmacher; Christian Grimme (ICWSM, 2023)

Lost in Transformation: Rediscovering LLM-Generated Campaigns in Social Media. - Britta Grimme; Janina Pohl; Hendrik Winkelmann; Lucas Stampe; Christian Grimme (MISDOOM, 2023)

Towards Multimodal Campaign Detection: Including Image Information in Stream Clustering to Detect Social Media Campaigns. - Lucas Stampe; Janina Pohl; Christian Grimme (MISDOOM, 2023)

A study on the effects of normalized TSP features for automated algorithm selection. - Jonathan Heins; Jakob Bossek; Janina Pohl; Moritz Seiler; Heike Trautmann; Pascal Kerschke (Theor. Comput. Sci., 2023)