Search Results for author: Federico Nanni

Found 16 papers, 8 papers with code

Overview of the CLPsych 2022 Shared Task: Capturing Moments of Change in Longitudinal User Posts

no code implementations NAACL (CLPsych) 2022 Adam Tsakalidis, Jenny Chim, Iman Munire Bilal, Ayah Zirikly, Dana Atzil-Slonim, Federico Nanni, Philip Resnik, Manas Gaur, Kaushik Roy, Becky Inkster, Jeff Leintz, Maria Liakata

We provide an overview of the CLPsych 2022 Shared Task, which focusses on the automatic identification of ‘Moments of Change’ in lon- gitudinal posts by individuals on social media and its connection with information regarding mental health .

Creation and evaluation of timelines for longitudinal user posts

1 code implementation10 Mar 2023 Anthony Hills, Adam Tsakalidis, Federico Nanni, Ioannis Zachos, Maria Liakata

There is increasing interest to work with user generated content in social media, especially textual posts over time.

Identifying Moments of Change from Longitudinal User Text

no code implementations ACL 2022 Adam Tsakalidis, Federico Nanni, Anthony Hills, Jenny Chim, Jiayu Song, Maria Liakata

Identifying changes in individuals' behaviour and mood, as observed via content shared on online platforms, is increasingly gaining importance.

DeezyMatch: A Flexible Deep Learning Approach to Fuzzy String Matching

1 code implementation EMNLP 2020 Kasra Hosseini, Federico Nanni, Mariona Coll Ardanuy

We present DeezyMatch, a free, open-source software library written in Python for fuzzy string matching and candidate ranking.

Transfer Learning

A Deep Learning Approach to Geographical Candidate Selection through Toponym Matching

2 code implementations17 Sep 2020 Mariona Coll Ardanuy, Kasra Hosseini, Katherine McDonough, Amrey Krause, Daniel van Strien, Federico Nanni

We report its performance on candidate selection in the context of the downstream task of toponym resolution, both on existing datasets and on a new manually-annotated resource of nineteenth-century English OCR'd text.

Entity Resolution Optical Character Recognition (OCR) +1

Policy Preference Detection in Parliamentary Debate Motions

no code implementations CONLL 2019 Gavin Abercrombie, Federico Nanni, Riza Batista-Navarro, Simone Paolo Ponzetto

Debate motions (proposals) tabled in the UK Parliament contain information about the stated policy preferences of the Members of Parliament who propose them, and are key to the analysis of all subsequent speeches given in response to them.

General Classification Test

Computational Analysis of Political Texts: Bridging Research Efforts Across Communities

no code implementations ACL 2019 Goran Glava{\v{s}}, Federico Nanni, Simone Paolo Ponzetto

Political scientists created resources and used available NLP methods to process textual data largely in isolation from the NLP community.

Stance Detection

Political Text Scaling Meets Computational Semantics

2 code implementations12 Apr 2019 Federico Nanni, Goran Glavas, Ines Rehbein, Simone Paolo Ponzetto, Heiner Stuckenschmidt

During the last fifteen years, automatic text scaling has become one of the key tools of the Text as Data community in political science.

feature selection

Event-based Access to Historical Italian War Memoirs

no code implementations8 Apr 2019 Marco Rovera, Federico Nanni, Simone Paolo Ponzetto

The progressive digitization of historical archives provides new, often domain specific, textual resources that report on facts and events which have happened in the past; among these, memoirs are a very common type of primary source.

Topic-Based Agreement and Disagreement in US Electoral Manifestos

no code implementations EMNLP 2017 Stefano Menini, Federico Nanni, Simone Paolo Ponzetto, Sara Tonelli

We present a topic-based analysis of agreement and disagreement in political manifestos, which relies on a new method for topic detection based on key concept clustering.


Cross-Lingual Classification of Topics in Political Texts

no code implementations WS 2017 Goran Glava{\v{s}}, Federico Nanni, Simone Paolo Ponzetto

In this paper, we propose an approach for cross-lingual topical coding of sentences from electoral manifestos of political parties in different languages.

General Classification Text Classification +2

Unsupervised Cross-Lingual Scaling of Political Texts

1 code implementation EACL 2017 Goran Glava{\v{s}}, Federico Nanni, Simone Paolo Ponzetto

Political text scaling aims to linearly order parties and politicians across political dimensions (e. g., left-to-right ideology) based on textual content (e. g., politician speeches or party manifestos).

Entities as topic labels: Improving topic interpretability and evaluability combining Entity Linking and Labeled LDA

no code implementations26 Apr 2016 Federico Nanni, Pablo Ruiz Fabo

In order to create a corpus exploration method providing topics that are easier to interpret than standard LDA topic models, here we propose combining two techniques called Entity linking and Labeled LDA.

Descriptive Entity Linking +1

Cannot find the paper you are looking for? You can Submit a new open access paper.