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
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