2nd Workshop on Novel Evaluation Approaches for Text Classification Systems
Co-located with ICWSM 2023, 5 June 2023, Limassol, Cyprus
CALL FOR PARTICIPATION
Welcome to SemEval 2022 Task 4: Patronizing and Condescending Language Detection
We invite all researchers interested in text classification, bias detection and NLP for social impact to participate in SemEval 2022 - Task 4, which is focused on detecting and categorizing Patronizing and Condescending Language (PCL) towards vulnerable communities.
Detailed information about the task can be found in the following links:
Event information detection consists of multiple subsequent steps that could drastically affect the quality of the resulted event database. Thus, we believe one must consider a complete scenario that consists of document and sentence classification as relevant or not, event coreference resolution, event information extraction, and event classification in relation to an event taxonomy, and test the results on a list of events created manually to determine performance of the state-of-the-art on this task.
Today, the unprecedented quantity of easily accessible data on social, political, and economic processes offers ground-breaking potential in guiding data-driven analysis in social and human sciences and in driving informed policy-making processes. The need for precise and high-quality information about a wide variety of events ranging from political violence, environmental catastrophes, and conflict, to international economic and health crises has rapidly escalated (Porta and Diani, 2015; Coleman et al. 2014).
We invite contributions from researchers in computer science, NLP, ML, AI, socio-political sciences, conflict analysis and forecasting, peace studies, as well as computational social science scholars involved in the collection and utilization of socio-political event data. Social and political scientists will be interested in reporting and discussing their approaches and observe what the state-of-the-art text processing systems can achieve for their domain.
Automatic Extraction of Socio-Political Events from News (AESPEN) is a workshop, which promotes the advances and synergies in the field of detection of socio-political events, creation of new event datasets, developments of new approaches and systems, based on state-of-the art machine learning (ML) and Natural Language Processing (NLP) technologies in the scope of Language Resources and Evaluation Conference (LREC 2020).
Collecting protest and conflict event information from news sources enables historical and comparative studies of social movements in social and political sciences. As the collection of event data covers more countries, longer time periods, and more details and granularity, which are more abound in local sources in comparison to international resources, their utility in social science applications multiplies.
GermEval 2019 Task 1 - Shared Task on hierarchical classification of German blurbs (short texts)
We invite interested parties from academia and industry to participate in this shared task. Further information can be found here: https://competitions.codalab.org/competitions/21226.
The workshop addresses the increasing relevance of natural language processing (NLP) for regional, national and international economy, both in terms of already launched language technology products and systems, as well as new methodologies and techniques emerging in interaction with the paradigm of Computational Social Science. The focus of the workshop is on the many ways, how NLP alters business relations and procedures, economic transactions, and the roles of human and computational actors involved in commercial activities.
BioASQ challenge on large-scale biomedical semantic indexing and question answering
(part of the CLEF 2015 QA track to take place in Toulouse, France, 8-11 September, 2015)
Web site: http://bioasq.org/
twitter: https://twitter.com/bioasq
CLEF-QA site: http://nlp.uned.es/clef-qa/
The BioASQ challenge consists of two different tasks (Task 3a and Task 3b).
If you are interested in any of the following areas:
* Large-scale and hierarchical classification
* Machine learning
* Semantic Indexing, semantic similarity
