This overview presents the Author Profiling shared task at PAN 2022. This year’s task (IROSTEREO) focuses on determining whether the author of a Twitter feed is keen to spread irony and stereotypes. The main aim is to show the feasibility of automatically identifying potential Twitter users that spread stereotypes using indirect speech such as irony. For this purpose, a corpus with Twitter data in English has been provided. Altogether, the approaches of 64 participants have been evaluated. Moreover, a subtask on profiling stereotype stance at author level was also proposed in order to see if stereotypes have been employed by ironic authors to hurt the possible targets (e.g. immigrants, women, the LGTB+ community, etc.) or, on the contrary, to support them.
Ortega-Bueno, R., Chulvi, B., Rangel, F., Rosso, P., Fersini, E. (2022). Profiling Irony and Stereotype Spreaders on Twitter (IROSTEREO). Overview for PAN at CLEF 2022. In 2022 Conference and Labs of the Evaluation Forum, CLEF 2022 (pp.2314-2343). CEUR-WS.
Profiling Irony and Stereotype Spreaders on Twitter (IROSTEREO). Overview for PAN at CLEF 2022
Fersini E.
2022
Abstract
This overview presents the Author Profiling shared task at PAN 2022. This year’s task (IROSTEREO) focuses on determining whether the author of a Twitter feed is keen to spread irony and stereotypes. The main aim is to show the feasibility of automatically identifying potential Twitter users that spread stereotypes using indirect speech such as irony. For this purpose, a corpus with Twitter data in English has been provided. Altogether, the approaches of 64 participants have been evaluated. Moreover, a subtask on profiling stereotype stance at author level was also proposed in order to see if stereotypes have been employed by ironic authors to hurt the possible targets (e.g. immigrants, women, the LGTB+ community, etc.) or, on the contrary, to support them.
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