Abstract
Sifting French Tweets to Investigate the Impact of Covid-19 in Triggering Intense Anxiety. Social media can be leveraged to understand public sentiment and feelings in real-time, and target public health messages based on user interests and emotions. In this paper, we investigate the impact of the COVID-19 pandemic in triggering intense anxiety, relying on messages exchanged on Twitter. More specifically, we provide : i) a quantitative and qualitative analysis of a corpus of tweets in French related to coronavirus, and ii) a pipeline approach (a filtering mechanism followed by Neural Network methods) to satisfactory classify messages expressing intense anxiety on social media, considering the role played by emotions.- Anthology ID:
- 2021.jeptalnrecital-taln.21
- Volume:
- Actes de la 28e Conférence sur le Traitement Automatique des Langues Naturelles. Volume 1 : conférence principale
- Month:
- 6
- Year:
- 2021
- Address:
- Lille, France
- Editors:
- Pascal Denis, Natalia Grabar, Amel Fraisse, Rémi Cardon, Bernard Jacquemin, Eric Kergosien, Antonio Balvet
- Venue:
- JEP/TALN/RECITAL
- SIG:
- Publisher:
- ATALA
- Note:
- Pages:
- 219–226
- Language:
- URL:
- https://aclanthology.org/2021.jeptalnrecital-taln.21
- DOI:
- Cite (ACL):
- Mohamed Amine Romdhane, Elena Cabrio, and Serena Villata. 2021. Sifting French Tweets to Investigate the Impact of Covid-19 in Triggering Intense Anxiety. In Actes de la 28e Conférence sur le Traitement Automatique des Langues Naturelles. Volume 1 : conférence principale, pages 219–226, Lille, France. ATALA.
- Cite (Informal):
- Sifting French Tweets to Investigate the Impact of Covid-19 in Triggering Intense Anxiety (Amine Romdhane et al., JEP/TALN/RECITAL 2021)
- PDF:
- https://preview.aclanthology.org/emnlp-22-attachments/2021.jeptalnrecital-taln.21.pdf