9 citations · 26 across the 7 of their papers we have counts for
8 papers
Creation and evaluation of timelines for longitudinal user posts
Anthony Hills, Adam Tsakalidis, Federico Nanni +2
There is increasing interest to work with user generated content in social media, especially textual posts over time. Currently there is no consistent way of segmenting user posts…
Identifying Moments of Change from Longitudinal User Text
Adam Tsakalidis, Federico Nanni, Anthony Hills +3
Identifying changes in individuals' behaviour and mood, as observed via content shared on online platforms, is increasingly gaining importance. Most research to-date on this topic…
A Deep Learning Approach to Geographical Candidate Selection through Toponym Matching
Mariona Coll Ardanuy, Kasra Hosseini, Katherine McDonough +3
Recognizing toponyms and resolving them to their real-world referents is required for providing advanced semantic access to textual data. This process is often hindered by the high…
Living Machines: A study of atypical animacy
Mariona Coll Ardanuy, Federico Nanni, Kaspar Beelen +7
This paper proposes a new approach to animacy detection, the task of determining whether an entity is represented as animate in a text. In particular, this work is focused on atypi…
Political Text Scaling Meets Computational Semantics
Federico Nanni, Goran Glavas, Ines Rehbein +2
During the last fifteen years, automatic text scaling has become one of the key tools of the Text as Data community in political science. Prominent text scaling algorithms, however…
Event-based Access to Historical Italian War Memoirs
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 th…
Benchmark for Complex Answer Retrieval
Federico Nanni, Bhaskar Mitra, Matt Magnusson +1
Retrieving paragraphs to populate a Wikipedia article is a challenging task. The new TREC Complex Answer Retrieval (TREC CAR) track introduces a comprehensive dataset that targets…
Entities as topic labels: Improving topic interpretability and evaluability combining Entity Linking and Labeled LDA
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…