Papers by Davide Picca
WeDH - a Friendly Tool for Building Literary Corpora Enriched with Encyclopedic Metadata (2020.lrec-1)
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| Challenge: | Linked Open Data repositories are difficult to use for text corpora enriched with metadata . a collaborative project aims to fill the access to textual resources available on the web and the possibility of combining these resources with sources of metadata extending the life and maintenance of the data itself. |
| Approach: | They propose a web interface that allows users to leverage encyclopedic knowledge from DBpedia, wikidata and VIAF to enrich texts with bibliographical and exegetical knowledge. |
| Outcome: | WeDH aims to fill the access to textual resources available on the web and the possibility of combining these resources with sources of metadata that can enrich the texts with useful information. |
Deciphering Emotional Landscapes in the Iliad: A Novel French-Annotated Dataset for Emotion Recognition (2024.lrec-main)
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| Challenge: | Using an emotion-annotated dataset, we aim to provide a resource for the scientific community to study the emotional intricacies of classical literature. |
| Approach: | They propose to provide an emotion-annotated dataset for classical literature and Western mythology using a multivariate time series and a deep learning masked language model. |
| Outcome: | The proposed dataset reveals compelling patterns and phenomena within the Iliad's emotional landscape. |
Sentiment Analysis of Homeric Text: The 1st Book of Iliad (2022.lrec-1)
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| Challenge: | Sentiment analysis studies focus more on online customer reviews and social media texts, but are less on literary studies. |
| Approach: | They propose to model the perceived sentiment of Iliad verses using a deep learning masked language model and a pre-trained model to estimate the sentiment of the poem. |
| Outcome: | The proposed model shows that sentiment estimators can be used as mechanical annotators, thus facilitating the distant reading of Homeric text. |
ME2-BERT: Are Events and Emotions what you need for Moral Foundation Prediction? (2025.coling-main)
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| Challenge: | Existing methods for moral foundation prediction are limited due to lack of annotated data. |
| Approach: | They propose a framework for fine-tuning a pre-trained language model to the task of moral foundation prediction. |
| Outcome: | The proposed framework outperforms state-of-the-art methods for moral foundation prediction with an average increase of 35% in the out-of domain scenario. |