Research Projects Tilburg center for Cognition and Communication
This page lists some recent and ongoing externally funded projects that are carried out at the Tilburg center for Cognition and Communication (TiCC)
Discussion Thread Summarization for Mobile Devices
("DISCO-SUMO"; NWO Creative Industries programme; 2015-2018)
People access the internet increasingly through mobile devices and simultaneously spend more time reading social media than traditional media.
One of the important functions of discussion and review websites is to facilitate social interaction in the form of discussions. However, the structure of the discussions and reviews posted on these websites is difficult to render on mobile devices. They can be long, and the highlights can be hidden anywhere in the thread. A small screen is a serious hindrance to searching and browsing in this mass of text.
To address this problem a team of researchers from Radboud University, Tilburg University, and Sanoma Media BV will develop a new discussion thread summarizer, which will allow mobile users to quickly digest the key points of a discussion thread as it has developed so far, thereby making it easier for users to contribute. As a result, the threshold for mobile users to participate in online discussions will be significantly lowered, and the general quality and understanding of these discussions may be expected to increase.
Political Apologies across Cultures
("APOLOGY"; ERC-Consolidator Grant; 2016-2021)
In the past decades, there has been a considerable rise in the number of apologies offered by states for injustices and human rights violations. At present, however, we do not know whether political apologies are a universally viable way to restore justice and harmony.
This project addresses this challenge. Using an innovative, interdisciplinary, and multi-method approach with in-depth interviews, (experimental) surveys, and content analyses of apologies, it will be analyzed whether there are universals in how political apologies are valued, expressed, and interpreted or whether this varies as a function of cross-cultural differences in key values (collectivism and individualism) and norms (face and honor). Based on the findings, we will build a theoretical framework regarding the potential value and role of apologies in transitional justice processes.
Producing affective language
(NWO Free Competition Humanities; 2015-2019)
This projects aims to investigate (1) how the emotional states of speakers influence the language they produce and (2) how the influence of emotion on language production can be modeled in computational tools for affective natural language generation.
Specifically, we ask both whether content selection ("deciding what to say") and message formulation ("deciding how to say it") are affected by emotional appraisals of the language user. This will be studied in a series of experiments, zooming in on referential communication. The experimental findings will feed into the development of a novel automatic news report generation tool that can adjust the message depending on the emotion it is intended to reflect.
Second Language Tutoring using Social Robots
("L2TOR"; H2020; 2016-2018)
L2TOR (pronounced ‘el tutor’) is a scientific research project, called Second Language Tutoring using Social Robots, funded by the Horizon 2020 programme of the European Commission. The project aims to design a child-friendly tutor robot that can be used to support teaching preschool children a second language (L2) by interacting with children in their social and referential world.
Project website: http://www.l2tor.eu/
Affective Language Production: Content selection, message formulation and computational modelling
(ALP, NWO Free Competition)
In this project we study how speaker’s emotional state influences the language that they produce, looking both at the early stages (content selection) and later stages of language production (message formulation). In addition, we develop a computational model that generates emotionally charged texts, paving the way for targeted news-reporting.
Understanding cancer treatment data: Using data science to help cancer patients during treatment decision making
After a cancer diagnosis, oncologists are obliged to inform patients about the chances of a favourable effect (e.g., long-term survival) and the risks of adverse effects (e.g., death, side-effects) of treatment options. The aim of this project is to analyse the data of millions of Dutch cancer patients, determining what the pros and cons of different treatment options are for individual patients, and automatically presenting individualised predictions, with the aim of facilitating shared decision making.
Vlogging for a healthier food intake
(NWO, Veni, 2020-2024).
Nowadays, children consume insufficient fruit and vegetables, that eventually causes multiple chronic diseases. The current project develops and investigates a new overarching theoretical model that explains and predicts whether, how, when, and for whom food-promotion techniques increase children’s fruit and vegetables intake, both on the short- and long-term.