Sardistance@ evalita2020: Overview of the task on stance detection in italian tweets
SardiStance is the first shared task for Italian on the automatic classification of stance in
tweets. It is articulated in two different settings: A) Textual Stance Detection, exploiting only …
tweets. It is articulated in two different settings: A) Textual Stance Detection, exploiting only …
Preserving integrity in online social networks
Preserving integrity in online social networks Page 1 92 COMMUNICATIONS OF THE ACM |
FEBRUARY 2022 | VOL. 65 | NO. 2 review articles THE GOAL OF online social networks is to …
FEBRUARY 2022 | VOL. 65 | NO. 2 review articles THE GOAL OF online social networks is to …
The importance of modeling social factors of language: Theory and practice
Natural language processing (NLP) applications are now more powerful and ubiquitous
than ever before. With rapidly developing (neural) models and ever-more available data …
than ever before. With rapidly developing (neural) models and ever-more available data …
Knowledge enhanced masked language model for stance detection
K Kawintiranon, L Singh - Proceedings of the 2021 conference of …, 2021 - aclanthology.org
Detecting stance on Twitter is especially challenging because of the short length of each
tweet, the continuous coinage of new terminology and hashtags, and the deviation of …
tweet, the continuous coinage of new terminology and hashtags, and the deviation of …
Multilingual stance detection in social media political debates
Stance Detection is the task of automatically determining whether the author of a text is in
favor, against, or neutral towards a given target. In this paper we investigate the portability of …
favor, against, or neutral towards a given target. In this paper we investigate the portability of …
Dynamic contextualized word embeddings
Static word embeddings that represent words by a single vector cannot capture the
variability of word meaning in different linguistic and extralinguistic contexts. Building on …
variability of word meaning in different linguistic and extralinguistic contexts. Building on …
Graph-based modeling of online communities for fake news detection
Over the past few years, there has been a substantial effort towards automated detection of
fake news on social media platforms. Existing research has modeled the structure, style …
fake news on social media platforms. Existing research has modeled the structure, style …
Suicide ideation detection via social and temporal user representations using hyperbolic learning
Recent psychological studies indicate that individuals exhibiting suicidal ideation
increasingly turn to social media rather than mental health practitioners. Personally …
increasingly turn to social media rather than mental health practitioners. Personally …
Identifying the adoption or rejection of misinformation targeting covid-19 vaccines in twitter discourse
M Weinzierl, S Harabagiu - Proceedings of the ACM Web Conference …, 2022 - dl.acm.org
Although billions of COVID-19 vaccines have been administered, too many people remain
hesitant. Misinformation about the COVID-19 vaccines, propagating on social media, is …
hesitant. Misinformation about the COVID-19 vaccines, propagating on social media, is …
Predicting viral rumors and vulnerable users with graph-based neural multi-task learning for infodemic surveillance
In the age of the infodemic, it is crucial to have tools for effectively monitoring the spread of
rampant rumors that can quickly go viral, as well as identifying vulnerable users who may be …
rampant rumors that can quickly go viral, as well as identifying vulnerable users who may be …