List of results published directly linked with the projects co-funded by the Spanish Ministry of Economy and Competitiveness under the María de Maeztu Units of Excellence Program (MDM-2015-0502).

List of publications acknowledging the funding in Scopus.

The record for each publication will include access to postprints (following the Open Access policy of the program), as well as datasets and software used. Ongoing work with UPF Library and Informatics will improve the interface and automation of the retrieval of this information soon.

The MdM Strategic Research Program has its own community in Zenodo for material available in this repository   as well as at the UPF e-repository   

 

 

Back Barbieri F, Marujo L, Karuturi P, Brendel W. Multi-task Emoji Learning. 1st International Workshop on Emoji Understanding and Applications in Social Media. Co-located with The 12th International AAAI Conference on Web and Social Media (ICWSM-18)

Barbieri F, Marujo L, Karuturi P, Brendel W. Multi-task Emoji Learning. 1​st​ International Workshop on Emoji Understanding and Applications in Social Media. Co-located with The 12​th​ International AAAI Conference on Web and Social Media (ICWSM-18)

Emojis are very common in social media and understanding their underlying semantics is of great interest from a Natural Language Processing point of view. In this work, we investigate emoji prediction in short text messages using a multi-task pipeline that simultaneously predicts emojis, their categories and sub-categories. The categories are either manually predefined in the unicode standard or automatically obtained by clustering over word embeddings. We show that using this categorical information adds meaningful information, thus improving the performance of emoji prediction task. We systematically analyze the performance of the emoji prediction task by varying the number of training samples and also do a qualitative analysis by using attention weights from the prediction task

http://knoesis.org/resources/Emoji2018/Emoji2018_Papers/Paper6_Emoji2018.pdf