In the 4th ICWSM 2023 data challenge, we invite papers that model and contribute to understanding the temporal and social dynamics of the social tasks in the provided datasets, or identify other important related dimensions to study the temporal effect on those datasets.

We welcome submissions on topics including - but not limited to -

-Task1 : Leveraging the evolution in time for specific task.

We encourage submissions that characterize the incorporation of temporal data in different social-based tasks, both at data and model level. Tasks may include, but are not limited to, modeling temporal characteristics of hate speech, using different versions of edited Wikipedia articles, enhanced tone detection, the effectiveness of temporal data in detecting the veracity of rumors, and stance detection dynamics. Submitted papers may focus on evaluating models' performance when considering the time variable, studying the evolution of specific phenomena, examining the distribution shift between the training data and live update data, or focusing on specific concept shifts.


-Task2: Studying trends and social change.

We especially welcome contributions that examine the transitions in community or content based on social data (i.e., temporal networks or content) to analyze some social phenomena. For example, studying context or static embedding to analyze content across time and communities where the main goal could be to study changes in descriptions of genders and ethnic groups, representation of people using contextualized semantics, analyzing factors that cause the formation and persistence of trends, the dynamics of sentiment and topics, or the manifestation of different social phenomena across communities.


Further detail about the Data Challenge

https://sites.google.com/view/icwsm2023datachallenge/home

ICWSM 2023 Data challenge