Papers by Federico Nanni
DeezyMatch: A Flexible Deep Learning Approach to Fuzzy String Matching (2020.emnlp-demos)
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| Challenge: | DeezyMatch is a free, open-source software library written in Python for fuzzy string matching and candidate ranking. |
| Approach: | They propose to use DeezyMatch to train new classifiers and fine-tune a pretrained model to generate rich vector representations from string inputs. |
| Outcome: | The proposed algorithm can be used to find the best matching candidates in large knowledge bases and query sets. |
When Time Makes Sense: A Historically-Aware Approach to Targeted Sense Disambiguation (2021.findings-acl)
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Kaspar Beelen, Federico Nanni, Mariona Coll Ardanuy, Kasra Hosseini, Giorgia Tolfo, Barbara McGillivray
| Challenge: | a new paper examines whether making NLP models sensitive to time improves their performance . timesensitive Sense Disambiguation is a variation on Word Sense disambiguation . authors present a task to determine whether a token in a text is related to a specific sense . |
| Approach: | They propose a task to determine whether a token in a text is related to a specific sense of a lemma. |
| Outcome: | The proposed model improves when time sensitive, rather than historically-aware, models . the proposed model is a variation on Word Sense Disambiguation (WSD) the proposed method is of more practical relevance to digital history and cultural analysis . |
Computational Analysis of Political Texts: Bridging Research Efforts Across Communities (P19-4)
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| Challenge: | Political scientists have developed and adopted natural language processing (NLP) methods to exploit text as an additional source of data in their analyses. |
| Approach: | This tutorial aims to provide a gentle introduction to methods and tasks related to computational analysis of political texts from both communities. |
| Outcome: | The main goal of this tutorial is to bring the two research communities closer to each other and contribute to faster and more significant developments in this interdisciplinary area. |
Identifying Moments of Change from Longitudinal User Text (2022.acl-long)
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| Challenge: | Identifying changes in individuals’ behaviour and mood via shared content is gaining importance given the global increase in mental health disorders and the limited access to support services. |
| Approach: | They propose a task of identifying moments of change in individuals on the basis of their shared content online. |
| Outcome: | The proposed task is based on 500 manually annotated user timelines and shows that it performs best through context aware sequential modelling. |
Creation and evaluation of timelines for longitudinal user posts (2023.eacl-main)
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| Challenge: | Existing methods for segmenting user posts into timelines improve quality and cost of manual annotation. |
| Approach: | They propose a set of methods for segmenting longitudinal user posts into timelines likely to contain interesting moments of change in a user’s behaviour based on their online posting activity. |
| Outcome: | The proposed framework is able to evaluate two different social media datasets and compares with existing models. |
Living Machines: A study of atypical animacy (2020.coling-main)
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Mariona Coll Ardanuy, Federico Nanni, Kaspar Beelen, Kasra Hosseini, Ruth Ahnert, Jon Lawrence, Katherine McDonough, Giorgia Tolfo, Daniel CS Wilson, Barbara McGillivray
| Challenge: | atypical animacy is the property of being alive, but discrepancies are not uncommon . a typical animate is represented as either animate or inanimate in a text . |
| Approach: | They propose a method for determining whether an entity is represented as animate in a text . they use a nineteenth-century English text to analyze animacy . |
| Outcome: | The proposed method improves on an established animacy dataset and a newly introduced resource. |