Tuesday, 2 December 2025



Exploring the Digital Identity of Agrifood Products: 

My ATRIUM TNA Placement at the GATE Group


By Tenia Panagiotou

As a linguist and postdoctoral researcher at the Consumer and Sensory Lab of the Department of Food Science and Nutrition, University of the Aegean, my work sits at the intersection of language, food, and digital communication. Over the past year, my research has focused on the digital identity of agrifood products – how olive oil, wine, honey, cheese, herbs, and other regional products are portrayed online, how consumers talk about them, and how professionals frame them through branding, marketing narratives, and cultural references. Understanding this “digital identity” requires robust, scalable data extraction and analysis pipelines – something that text mining and AI tools can powerfully enhance.

Through the Transnational Access scheme of the ATRIUM, I had the opportunity to return to the School of Computer Science at the University of Sheffield for a two-week placement (17–28 November 2025). My goal this time was more targeted than during my previous visit. Whereas my earlier placement focused on exploring tools, this one focused on building and evaluating an operational pipeline for analysing agrifood discourse across social media and web sources.


A building with a lawn and a bench

AI-generated content may be incorrect.A sign on a wall

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School of Computer Science, University of Sheffield


Developing and Validating a Multi-Layer Analytical Pipeline

During this visit, I worked closely with the GATE/CLARIN-UK team (special thanks go to Xingyi Song and Ian Roberts) to refine the multi-step data acquisition and analysis pipeline I presented at the beginning of my stay. This placement concentrated on building and evaluating an operational pipeline for analysing agrifood discourse across social media and web sources. This work forms a foundational part of our broader effort to understand how food products acquire and project their digital identity in consumer-driven environments.A group of people standing in a room

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Members of the GATE team


As the first analytical layer, I assessed food relatedness, distinguishing posts that genuinely concern food products from those that only mention them peripherally. This was followed by sentiment analysis (positive, negative, neutral) and a more granular classification of emotions using the food-elicited emotion lexicon developed by our team. This dual approach allowed us to capture both surface-level sentiment and more nuanced affective responses associated with agrifood products.

This visit has once again demonstrated the value of interdisciplinary cooperation in addressing complex, data-intensive challenges in food communication and consumer behaviour. I look forward to extending our partnership with the GATE group as we continue building tools and methodologies for understanding online food discourse – an emerging area at the intersection of linguistics, AI, and food science.


A screenshot of a computer

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Screenshot of pipeline output regarding emotion


A significant part of the workflow involved classifying posts against the 17 United Nations Sustainable Development Goals, allowing us to investigate how sustainability narratives intersect with agricultural food product promotion and consumer expression. In parallel, I applied structured evaluations of health claims (healthy / unhealthy / neither), and identified mentions of nutritional content using recognised nutritional-claim terminology from the literature. Posts were also categorised by diet style, based on the most common diet-related expressions appearing in Greek online food discourse.

The pipeline further incorporated several agrifood-specific layers. These included the identification of sponsored versus non-sponsored posts; extraction of sensory attributes using the ISO sensory-analysis vocabulary; and topic classification using a controlled vocabulary derived from the LanguaL™ food-description thesaurus, an established international standard for structured food categorisation. Additional layers captured time expressions, Protected Designation of Origin/Protected Geographical Indication references, the 13 official Greek prefectures for locality insights, and standard olive oil types, given the prominence of olive-oil content in our dataset.

Together, these components form a comprehensive analytical framework that supports direct comparison between human classification, and AI-driven open-response versus closed-set classification. This comparison will allow us to quantify alignment, divergence, and the specific areas where Large Language Model (LLM)-based classification performs strongly or reveals fragility when applied to Greek agrifood discourse. This will allow us to choose the best route considering the pros and cons of each method. The placement offered the environment and technical guidance required to validate the pipeline, evaluate model behaviour, and refine the overall architecture for future tool development and collaborative research.

A screenshot of a computer

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Pic.5: Screenshot of pipeline output regarding sensory attributes


Technical Discussions and Next Steps

Beyond the core analysis, the visit provided valuable opportunities for in-depth discussions with GATE researchers about potential tool development and methodological extensions. We reviewed infrastructure constraints, data-format interoperability issues, and strategies for orchestrating multi-step processing within the GATE ecosystem. These conversations will directly shape the next phase of collaboration, guiding both immediate refinements and the longer-term agenda for joint work.

Throughout my stay, the GATE team was extremely supportive, offering expert advice on evaluation frameworks, debugging strategies, and LLM behaviour in multi-label tasks. The environment was collaborative, constructive, and intellectually stimulating. These two weeks enabled me not only to strengthen the methodological aspects of the project but also to strategically plan our next steps, including joint publications, shared datasets, and the creation of specialised agrifood-oriented NLP tools.

I am especially grateful to the ATRIUM programme for providing this opportunity; to Diana Maynard for accepting me for a second visit and for her guidance and support; to Jo Wright for managing all logistics and securing the coziest accommodation for my stay. 


A street with lights and people walking

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A fountain in a park

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Christmassy Sheffield

This visit has once again demonstrated the value of interdisciplinary cooperation in addressing complex, data-intensive challenges in food communication and consumer behaviour. I look forward to extending our partnership with the GATE group as we continue building tools and methodologies for understanding online food discourse – an emerging area at the intersection of linguistics, AI, and food science.

Monday, 3 February 2025

Exploring NLP Applications in Food Research: my ATRIUM TNA visit to the GATE group

By Tenia Panagiotou

As a postdoctoral researcher at the Consumer and Sensory Lab of the Department of Food Science and Nutrition of the University of the Aegean, Greece, I study food consumption-related phenomena and consumer expression on social media. In this context, I find that Natural Language Processing (NLP) tools can significantly enhance data collection and analysis. With a background in linguistics, I explore how language can reveal insights into consumer behaviour, culture-specific and cross-cultural food-related trends, attitudes toward products and brands, and consumer expectations. To deepen my understanding of NLP tools and computational applications in social media research, I sought further training in this field.

Pic.1: Collecting posts on social media to investigate food related phenomena: sustainable meat alternatives (left), local versus imported cheeses (right).

The ATRIUM project through its TNA scheme has provided me with the invaluable opportunity to visit the School of Computer Science at the University of Sheffield and explore applications of the GATE cloud tools in my research. Although my visit was relatively short (January 20–31, 2025), it was exceptionally enlightening. I had the privilege of working closely with members of the GATE group, experts in NLP, who welcomed me into their working meetings, discussed my research challenges, and provided insightful solutions and guidance.


Pic. 2: My office away from home at the GATE headquarters (School of Computer Science, University of Sheffield). 

During my visit, I explored various GATE tools relevant to my research. Some of those tools were still under development, and the researchers were kind enough to grant me access, assist me in their application, and discuss possible extensions. One particularly useful tool was the Topic Extractor for social media hashtags, which can be used to analyze food consumption-related concepts and generate hierarchical concept graphs. The TwitIE Named Entity Recognizer proved particularly valuable in accurately identifying individual words within multiword hashtags—one of the key challenges I had been aiming to resolve. 




Pic. 3: Screenshot of the TwitIE Named Entity Recognizer that can identify words in multiword hashtags (last row).

Additionally, the Named Entity Recognizer offered significant insights by extracting predefined entities such as geopolitical locations, organizations, nationalities, and time references, enriching the analysis of consumer social media posts. I also explored sentiment analysis and opinion mining tools, while investigating how the user classification tool could be adapted for use across different platforms. Another intriguing discovery was the Multilingual Persuasion Technique Classifier, which presents exciting possibilities for analyzing professional posts on food products on social media.

 










Pic. 4: Identifying languages in posts, translating into English, and running Named Entity Recognition to be used for semantic network analysis. 

Beyond these tools, I also received valuable guidance on optimizing ChatGPT and Large Language Models for consistency in responses and on clustering social media post hashtags into semantically meaningful groups for further analysis. Both of these challenges were high on my research agenda, and I am grateful for the specialized insights I received. Apart from the technical expertise I gained, engaging in discussions on shared research interests, such as ontology and semantic network development, was one of the most rewarding aspects of my visit. The openness of the GATE team to exploring extensions of their existing tools and fostering future collaborations made this experience particularly enriching.

Pic. 5: St George's Church, a former parish church (now part of the University of Sheffield as a lecture theatre and student housing) has been my view from the office.

I am deeply grateful to the members of the GATE group for their time, generosity, and willingness to support me both technically and personally. A special thanks goes to Dr. Maynard, who oversaw my visit, for guiding my "investigations" and for our insightful conversations. I would also like to thank Mrs. Wright, research project assistant to the GATE group, for handling the logistical details of my trip and stay in Sheffield, as well as for helping out with the required documentation.

This visit was an invaluable experience that has significantly shaped my research perspective. I look forward to applying what I have learned and fostering further collaborations with the GATE team. I strongly believe that this will not be my last visit to the GATE infrastructure.


                  


Monday, 6 January 2025

GATE team hosts its first ATRIUM TNA research visit: Using NLP to understand trends in political and social debate

In December 2024, we hosted research visitor Tasos Galanopoulos as part of  the ATRIUM project (Advancing fronTier Research In the arts and hUManities) TransNational Access scheme. ATRIUM's aim is to bridge 4 leading research infrastructures in: arts and humanities (DARIAH), archaeology (ARIADNE), language technology (CLARIN), and open scholarly communication in the social sciences and humanities (OPERAS). The Transnational Access (TNA) scheme offers fully funded placements for researchers across Europe. This initiative is designed to support Arts and Humanities researchers by providing access to expert knowledge, mentorship, and tools from leading Data Management organisations. Successful applicants have the opportunity to visit one of 14 different host organisations across Europe in order to conduct their research, benefiting from direct contact, knowledge sharing and network building. 



Tasos describes his visit below...

How can NLP tools and large language models be used to understand trends in political and social debate around major issues of the day? 

 What is the relationship between 'distant reading' and the layered understanding that these tools offer for large volumes of data, and 'close reading', understanding aspects of these topical issues?  

What role can these modern tools play in the humanities and in everyday journalistic practice?  

Questions such as these, on the occasion of a project on "Analysis of textual data from newspapers on the agreement of Greece's accession to the European Economic Community EEC (1961)", in the context of my postgraduate studies in Digital Humanities at the Open University of Greece, brought me to the School of Computer Science at the University of Sheffield at the end of November (23/11/2024 - 7/12/2024), to collaborate with members of the GATE team.

Despite the short period of the stay, the impressions were the best: the patience and goodwill of all the team - with Dr Maynard at the forefront - helped me to "navigate" the tools offered by the GATE Cloud and the European Language Grid, to understand a bit better the processes required, and the wider field, to learn a bit more about its "alphabet" and requirements. At the same time, through the regular meetings of the team I was able to get a "glimpse" of the modern, specialised, and valuable research being carried out at the university.  


In relation to the actual subject of the research, the findings from the processing with tools such as NamedEntity Recognition, N-gram detection and their visualization with wordclouds, Topic Classification, Sentiment Analysis, Multidimensional analysis with LIWC-22, Persuasion techniques were very interesting, giving answers and insights to our questions that had to do with the attempt to develop a methodology to identify, document and frame named entities in the context of the investigation of public discourse, Press with different political orientation and political rhetoric in relation to critical events in political life, with reference to the economic and social environment inside and outside the country. Also "identifying" and categorising arguments for and against, and 'bias' for/against in the Press of that time and at a subsequent level , enabled us to explore ways to link entities to key concepts in argumentation.


 Overall, my impressions were therefore the best from this constructive visit, a visit that on a personal level gave me inspiration and opened new horizons, but also created new contacts with remarkable people.