Conspiracy theories are complex narratives that attempt to explain the ultimate causes of significant events as cover plots orchestrated by secret, powerful, and malicious groups. A challenging aspect of identifying conspiracy stems from the difficulty of distinguishing critical thinking from conspiratorial thinking. This distinction is vital because labeling a message as conspiratorial when it is only oppositional could drive those who were simply asking questions into the arms of the conspiracy communities.
At PAN 2024 we aim at analyzing texts that reflect oppositional thinking and contain either conspiracy or critical narratives: https://pan.webis.de/clef24/pan24-web/oppositional-thinking-analysis.html
The task will address two new challenges for the research community: (1) to distinguish the conspiracy narrative from other oppositional narratives that do not express a conspiracy mentality (i.e., critical thinking); and (2) to identify in online messages the key elements of a narrative that fuels the intergroup conflict in oppositional thinking. To this end we provide two Telegram text datasets, one English and one Spanish, and we propose two sub-tasks:
1. Distinguishing between critical and conspiracy texts, a binary classification task aimed at differentiating between critical messages that question major decisions in the public health domain, but do not promote a conspiracist mentality; and messages that view the pandemic or public health decisions as a result of a malevolent conspiracy by secret, influential groups.
2. Detecting elements of the oppositional narratives, a token-level classification task aimed at recognizing text spans corresponding to the key elements of oppositional narratives, where each annotation corresponds to a narrative element, and is described by its span and its category (there are six distinct span categories: AGENT, FACILITATOR, VICTIM, CAMPAIGNER, OBJECTIVE, NEGATIVE_EFFECT).
We propose the task both in English and in Spanish. Although we recommend to participate in both languages, it is possible to address the problem just in one language.
The training dataset (where the authors have been anonymised and neutral labels have been used) can be requested via Zenodo: https://zenodo.org/records/10680586
IMPORTANT DATES: February 20, 2024: Train data release May 30, 2024: Software submission deadline June 15, 2024: Participant paper submission Midnight CEST [submission] [paper template] July 1st, 2024: Peer review notification July 08, 2024: Camera-ready participant papers submission September 09-12, 2024: CLEF conference https://clef2024.imag.fr/
Paolo Rosso, co-organiser of the PAN task on Oppositional thinking analysis