We analyze the effect of further retraining BERT with different domain specific data as an unsupervised domain adaptation strategy for event extraction. Portability of event extraction models is particularly challenging, with large performance drops affecting data on the same text genres (eg, news). We present PROTEST-ER, a retrained BERT model for protest event extraction. PROTEST-ER outperforms a corresponding generic BERT on out-of-domain data of 8.1 points. Our best performing models reach 51.91-46.39 F1 across both domains
Workshop at 2016 Conference on Empirical Methods in Natural Language Processing (5 November 2016)We ...
International audienceThe state-of-the-art abusive language detection models report great in-corpus ...
This workshop is the fourth issue of a series of workshops on automatic extraction of sociopolitical...
We analyze the effect of further retraining BERT with different domain specific data as an unsupervi...
We analyze the effect of further retraining BERT with different domain specific data as an unsupervi...
This notebook describes our participation to the Protest- New Lab, identifying protest events in new...
2019 has been characterized by worldwide waves of protests. Each country’s protests is different but...
2019 has been characterized by worldwide waves of protests. Each country’s protests is different but...
This notebook describes our participation to the Protest- New Lab, identifying protest events in new...
We present a corpus for protest event mining that combines token-level annotation with the event sch...
Wiedemann G, Haunss S, Dollbaum JM, Daphi P, Meier LD. A Generalizing Approach to Protest Event Dete...
In this paper, we introduce HateBERT, a re-trained BERT model for abusive language detection in Engl...
For now more than four decades, quantitative protest event analysis (PEA) has routinely contributed ...
Protest event analysis is a key method to study social movements, allowing to systematically analyze...
An ever-increasing amount of text, in the form of social media posts and news articles, gives rise t...
Workshop at 2016 Conference on Empirical Methods in Natural Language Processing (5 November 2016)We ...
International audienceThe state-of-the-art abusive language detection models report great in-corpus ...
This workshop is the fourth issue of a series of workshops on automatic extraction of sociopolitical...
We analyze the effect of further retraining BERT with different domain specific data as an unsupervi...
We analyze the effect of further retraining BERT with different domain specific data as an unsupervi...
This notebook describes our participation to the Protest- New Lab, identifying protest events in new...
2019 has been characterized by worldwide waves of protests. Each country’s protests is different but...
2019 has been characterized by worldwide waves of protests. Each country’s protests is different but...
This notebook describes our participation to the Protest- New Lab, identifying protest events in new...
We present a corpus for protest event mining that combines token-level annotation with the event sch...
Wiedemann G, Haunss S, Dollbaum JM, Daphi P, Meier LD. A Generalizing Approach to Protest Event Dete...
In this paper, we introduce HateBERT, a re-trained BERT model for abusive language detection in Engl...
For now more than four decades, quantitative protest event analysis (PEA) has routinely contributed ...
Protest event analysis is a key method to study social movements, allowing to systematically analyze...
An ever-increasing amount of text, in the form of social media posts and news articles, gives rise t...
Workshop at 2016 Conference on Empirical Methods in Natural Language Processing (5 November 2016)We ...
International audienceThe state-of-the-art abusive language detection models report great in-corpus ...
This workshop is the fourth issue of a series of workshops on automatic extraction of sociopolitical...