CogNosco Lab

 

Directed by Professors Massimo Stella and Luigi Lombardi, CogNosco Lab is part of the Department of Psychology and Cognitive Science of the University of Trento and it is physically hosted in the QPSY Laboratory, Room C107, 1st Floor, Palazzo Fedrigotti, Rovereto. 

CogNosco Lab focuses on next-generation models for understanding psychological phenomena and cognitive mechanisms through unique, cutting-edge and innovative frameworks spanning mathematical psychology, cognitive data science and complex systems theory.

CogNosco Lab designs models dealing with psychological phenomena through quantitative techniques, including cognitive network science, network psychometrics, human-centered artificial intelligence (AI), Bayesian inference and categorical data estimations. In addition to achieving models endowed with computational power and mathematical elegance, we strive to produce data-informed insights based on psychological theories and enable further explorations, validations, interpretations and understanding of psychological phenomena.

Our signature models include the framework of multilayer cognitive networks for modelling language acquisition and clinical impairments, forma mentis networks for knowledge modelling and text analysis, network-based AI psychometrics for detecting emotional distress/creativity levels and personality traits from social media and fluency data, and Bayesian model for detecting cheating and academic fraud.

If interested in collaborating with our group, please get in touch via email!

CogNosco Lab develops quantitative frameworks for understanding psychological data and phenomena.

Our ideas, models and data insights are powered by:

Cognitive Network Science

Cognitive networks are distributed models of conceptual knowledge representing how concepts, ideas and words are linked with each other. The science of multilayer networks makes it possible to build large-scale models of human knowledge structured across multiple types of conceptual associations from semantics, phonology, memory, syntactic, visual cues, affect and many other cognitive relationships.

Our research aims to determine how this multilayer network structure influences language acquisition, use and decline. We also develop forma mentis networks as tools for performing natural language processing in interpretable ways. Importantly, the network paradigm provides unprecedented interpretability to user- and group-level data.

Areas of application:

Predicting early language learning

Understanding language pathologies

Creativity and multilayer networks

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AI Psychometrics and Machine Psychology

Artificial Intelligence (AI) is a quickly rising field at the interface of cognitive science and computer science. AI Psychometrics adopts AI for detecting the presence of psychological constructs in situations where standard psychometric scales could not be administered, e.g. in social media texts, suicide letters or when simply recalling emotional states.

In our research, we develop network-based AI psychometric models for determining personality traits like Openness-to-Experience, or emotional distress levels like anxiety, depression and stress, or facets of cognition like creativity levels starting from fluency data and while considering mental walks on feature-rich networks. We also strive to build machine psychology models assessing bias in large language models like ChatGPT and others.

Areas of application:

Stance detection in social media

Semantic frames and the gender gap

Key perceptions of STEM subjects

Mathematical Psychology and Psychometrics

Our research stream focuses on interrelated issues dealing with multivariate data analysis of discrete variables, fake data analysis, and new Monte-Carlo-like approaches to evaluate statistical models.  We aim to study and propose new formal models of higher-level cognition, such as decision strategies, induction, similarity evaluation, and classification.

Our research interest is in semantic memory and semantic representations in natural languages. In particular, we focus on problems that are related to how people categorize and integrate semantic information as well as probabilistic cues in concept name retrieval tasks. We also try to compare the results of our models  both using empirical data collected from real participants and Monte Carlo studies.

Areas of application:

Modelling base-level cognition

Dynamic modelling of cognition

Fake data evaluation

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Our Team at CogNosco Lab:

Massimo Stella PhD

Massimo Stella PhD

Lab Director

My research focuses on cognitive networks, AI psychometrics and knowledge modelling. My research aims to develop cognitive models centered around the complexity of the mind.

Edith Haim

Edith Haim

PhD Candidate in Cognitive Science

My research interests are in creativity, semantic network modelling and psycholinguistics. I work with Prof. Stella.

Luigi Lombardi PhD

Luigi Lombardi PhD

Lab Director

My research focuses on mathematical psychology and discrete data analysis/inference. My research aims to develop mathematical models for testing low/high cognitive processes.

Andrea Zagaria

Andrea Zagaria

PhD Candidate in Cognitive Science

My research is on personality psychology and psychometric measurement in clinical psychology/psychothraumatology. I am also interested in metascience and computational linguistics. I work with Prof. Lombardi.

Luciana Ciringione PhD

Luciana Ciringione PhD

Research Fellow in Psychometrics

My research interests are related to the cognitive and emotional functioning of the human mind under conditions of mild distress and psychopathology. I work with Prof. Stella.

Riccardo Improta

Riccardo Improta

Postgraduate Researcher in Psychometrics

With a background in data science and sociology, I am interested in using AI and psychometric tools. My current research lies in machine psychology for the COGNOSCO project. I work with Prof. Stella.
Owen Saunders

Owen Saunders

Visiting PhD Student in Computer Science

Based in the CC Lab, University of Exeter, I am interested in knowledge modelling, NLP and science innovation. I am co-supervised by Profs. Chico Camargo (CCLab), Adrian Currie (University of Exeter, UK), and Prof. Stella.
Kayina Abudurexiti

Kayina Abudurexiti

PhD Candidate in Psychology

My research interest is in psychometrics and interviews regarding positive traits, positive emotions, positive schooling, and their impacts on human flourishing. I work with Prof. Laura Franchin (Baby Lab, DIPSCO) and Prof. Stella.

Katherine Abramski

Katherine Abramski

Visiting PhD Student in AI for Society

I am interested in creating computational models of language and the mind using tools from network science, cognitive science, and AI. I am co-supervised by Prof. Giulio Rossetti (KDD Lab) and Prof. Stella.
Edoardo Sebastiano De Duro

Edoardo Sebastiano De Duro

MSc Student in Cognitive Science

I am interested in studying the behaviour of LLMs using psychological methods and/or Natural Language Processing tools. I work with Prof. Stella.
Enrique Taietta

Enrique Taietta

BSc Student in Psychology (STPC)

My research interests are AI, large language models and cognitive data science. I work with Prof. Stella.
Lorenzo Arena

Lorenzo Arena

MSc Student in Human-Computer Interactions

I am interested in mathematical psychology and modelling the human mind. I work with Prof. Lombardi.
Tiziano Gaddo

Tiziano Gaddo

BSc Student in Psychology and Cognitive Science

I am interested in computational modelling of language, AI and machine psychology. I work with Prof. Stella.
Isaia D'Onofrio

Isaia D'Onofrio

BSc Student in Psychology

I’m interested in bridging the realms of human psychology and cutting-edge technology. In particular, a deeper understanding of AI’s emotional intelligence. I work with Prof. Stella.
Matteo Vaccaro

Matteo Vaccaro

BSc Student in Psychology

My research interests are in semantic networks, large language models and machine psychology. I am passionate about the explanatory and predictive power of data analysis applied to Psychology. I work with Prof. Stella.

External Collaborating ECRs:

Salvatore Citraro, Researcher @ CNR

Arnaldo Santoro, PhD Candidate @ UniCaFoscari

Alessandro Scarano @ DIPSCO

 

 

Past Lab Members:

Asra Fatima (Now Data Scientist @ CitiBank); Simmi Marina Joseph (Now Data Scientist @ SWW); Martyna Wozniak; Brian Kieran; Oliver Baker, Jude Warner-Willich; Harry Wang; James Butler; Finley Gibson (Research Fellow at IDSAI, University of Exeter); Filippo Stanghellini.

 

 

Collabs with UniTN Faculty:

Prof. Giuseppe Alessandro Veltri

Full Professor @ Dept. of Sociology

Prof. Alessandro Grecucci

Director of CLIAN Lab

Prof. Laura Franchin

Director of Baby Lab.

Prof. Enrico Perinelli

National and International Collabs:

Prof. Giulio Rossetti

Senior Researcher and Lead of the Network Science group at KDD Lab.

Prof. Michael Vitevitch

Director of the Spoken Language Lab, Department of Psychology, University of Kansas, USA.

Prof. Yoed N. Kenett

Director of the Cognitive Complexity Lab, Technion, Israel.

Prof. Fabiana Zollo

Our research portfolio at CogNosco Lab:

SELECTED PUBLICATIONS

  • Stella, M., Citraro, S., Rossetti, G., Marinazzo, D., Kenett, Y. N., & Vitevitch, M. S. (2024). Cognitive modelling of concepts in the mental lexicon with multilayer networks: Insights, advancements, and future challenges. Psychonomic Bulletin & Review, 1-24. [Read paper here]. new
  • Zagaria, A. & Lombardi, L. (2024). A new perspective on trends in psychology. New Ideas in Psychology, 74, 101078 [Read paper here]. new
  • Citraro, S., Warner-Willich, J., Battiston, F., Siew, C. S., Rossetti, G., & Stella, M. (2023). Hypergraph models of the mental lexicon capture greater information than pairwise networks for predicting language learning. New Ideas in Psychology71, 101034. [Read paper here].
  • Calcagni’ A., Cao N., Rubaltelli E., & Lombardi L. (2022). A psychometric modeling approach to fuzzy rating data. Fuzzy Sets and Systems, 447, 76-99 [Read paper here].
  • Samuel, G., Stella, M., Beaty, R. E., & Kenett, Y. N. (2023). Predicting openness to experience via a multiplex cognitive network approach. Journal of Research in Personality104, 104369. [Read paper here].
  • D’Alessandro M., Radev S., Voss A., & Lombardi L. (2020). A Bayesian brain model of adaptive behavior: an application to the Wisconsin Card Sorting Task. PeerJ, 8:e10316, 1-32. [Read paper here]
  • Fatima, A., Li, Y., Hills, T. T., & Stella, M. (2021). DASentimental: Detecting Depression, Anxiety, and Stress in Texts via Emotional Recall, Cognitive Networks, and Machine Learning. Big Data and Cognitive Computing, 5(4), 77.
  • Teixeira, A. S., Talaga, S., Swanson, T. J., & Stella, M. (2021). Revealing semantic and emotional structure of suicide notes with cognitive network science. Scientific Reports, 11(1), 1-15.
  • Stella, M. (2020). Text-mining forma mentis networks reconstruct public perception of the STEM gender gap in social media. PeerJ Computer Science, 6, e295.
  • Stella, M., & Zaytseva, A. (2020). Forma mentis networks map how nursing and engineering students enhance their mindsets about innovation and health during professional growth. PeerJ Computer Science, 6, e255.
  • Stella, M. (2020). Social discourse and reopening after COVID-19. First Monday, 25(11).
  • Stella, M., Restocchi, V., & De Deyne, S. (2020). # lockdown: Network-enhanced emotional profiling in the time of Covid-19. Big Data and Cognitive Computing, 4(2), 14.
  • Stella, M., De Nigris, S., Aloric, A., & Siew, C. S. (2019). Forma mentis networks quantify crucial differences in STEM perception between students and experts. PloS one, 14(10), e0222870.

PAST PUBLICATIONS FROM OTHER LABS THAT GUIDE OUR FUTURE RESEARCH

Stella, M., Beckage, N. M., & Brede, M. (2017). Multiplex lexical networks reveal patterns in early word acquisition in children. Scientific reports, 7(1), 1-10.
Stella, M., Ferrara, E., & De Domenico, M. (2018). Bots increase exposure to negative and inflammatory content in online social systems. Proceedings of the National Academy of Sciences, 115(49), 12435-12440.
Stella, M., Beckage, N. M., Brede, M., & De Domenico, M. (2018). Multiplex model of mental lexicon reveals explosive learning in humans. Scientific reports, 8(1), 1-11.
Stella, M., & Kenett, Y. N. (2019). Viability in multiplex lexical networks and machine learning characterizes human creativity. Big Data and Cognitive Computing, 3(3), 45.

LATEST PRE-PRINTS

Semeraro, A., Vilella, S., Mohammad, S., Ruffo, G., & Stella, M. (2023). EmoAtlas: An emotional profiling tool merging psychological lexicons, artificial intelligence and network science.

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Join us at CogNosco Lab, University of Trento, Italy

CogNosco is Latin for “I know”, a name that fits our scope on cognitive data science and mathematical psychology.

Why the capital letter in Nosco? Because it also means “with us”, a reminder that we are keen on growing and exploring cognitive data science together with prospective MSc students, PhD candidates, postdocs and collaborators.

Please get in touch for any potential exciting collaboration.

We are physically hosted in the QPSY Laboratory, Room C107, First Floor, Centrale, Palazzo Fedrigotti, Rovereto, Italy. We have a nice room for lab meetings with desks and IT equipment, including a dedicated desktop machine for running intensive numerical simulations and data analyses. Our room includes also a small library with books about mathematical psychology, discrete maths and network science. Come say “hi” if you are curious!

BSc and MSc students can join us for supervision and internships. Both Directors have available positions for internships for the academic year 2023/2024. Please get in touch with us if interested. We accept also interns from the Data Science MSc programme (Prof. Stella is the DIPSCO delegate for this interdepartmental programme, send him any inquiry).

For prospective PhD students, you might want to check the PhD programme in Cognitive Science at the University of Trento, an innovative training in academic research and analysis of psychological phenomena. The PhD programme runs yearly and it requires a research programme, please get in touch if interested! Another opportunity for joining the lab is through PhD co-supervisions, which are becoming increasingly common in academia. Please check the national programme for Artificial Intelligence which runs yearly and provides several full fellowships on topics like cognitive data science, among others. In any case, please get in touch with us with a brief CV and a short research proposal.

For postdocs, Marie Curie Fellowships are a great way of securing a good position in a vibrant research lab. We also have openings for assegni di ricerca (research fellowships) which can be checked here

For visiting scholars, DIPSCO runs an internal track for inviting outstanding international researchers. Please get in touch if interested in applying and knowing more.

For early career researchers, please check these opportunities:

Young Researchers on Complex Systems Bridge Grants – Small funding for national and international research visits.

More vacancies might open in the future and will be advertised here on this page.

Discover what we do at CogNosco Lab:

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News and Lab Outputs:

August 2023: New paper out published on Physica A and let by ex lab member Kieran Brian. In the paper we introduce “mindset streams” as generalisations of semantic frames for detecting patterns of conflict in associating concepts via memory recalls. Read the paper here:

https://doi.org/10.1016/j.physa.2023.129074

May 2023: New paper published in Big Data and Cognitive Computing, led by Katherine Abramsky, about how ChatGPT models – GPT 3, 3.5 and 4 – display stereotypical associations about math anxiety like high school students’. Read the paper here.

 

May 2023: New paper out in New Ideas in Psychology led by our lab member Judy Warner-Willich about cognitive hypergraph networks predicting early language acquisition considerably better than pairwise networks.

https://www.sciencedirect.com/science/article/abs/pii/S0732118X23000272

February 2023: CompCog 23 – Complexity and Cognition was a success! This year’s edition was sponsored by DIPSCO and it had 40 researchers from all over the world discussing latest advancements in modelling psychological phenomena and linguistic data.

January 2023: New paper out on Nature Scientific Reports about feature-rich multiplex lexical networks, led by Salvatore Citraro, and in collaboration with Giulio Rossetti of KDD Lab, CNR (Salvatore’s main supervisor), Mike Vitevitch and myself.

https://www.nature.com/articles/s41598-022-27029-6

January 2023: Happy New Year! CogNosco Lab moves from the Computer Science Department, Uni of Exeter (UK), to the Department for Psychology and Cognitive Science, UniTrento, Italy.

 

September 2022: New paper out led by lab member Stefan Claus on applying cognitive network science and natural language processing to UK insurance transcripts, published on Future Internet. Read the paper here

September 2022: New library out! Together with Alfonso Semeraro, Salvatore Vilella, Saif Mohammad and Giancarlo Ruffo we released EmoAtlas (GitHub link: https://github.com/alfonsosemeraro/emoatlas) a tool for extracting emotions and forma mentis networks from text. Give it a try!  

August 2022: New paper out on the emotions of COVID-19 reliable and unreliable news media:

 https://www.nature.com/articles/s41598-022-18472-6 

 

 

July 2022: Our lab member Kieran Brian presents his research results about conflict in “math” and “fun” perceptions at NetSciEd 2022 with a contributed talk. Well done! 

June 2022: Thanks to an EPSRC Turing-Exeter Award, Finley Gibson joins the lab for working on forma mentis networks, in collaboration with Sarah Morgan, University of Cambridge.

 

May 2023: What feelings do people express in mental health subreddits about schizophrenia and other clinical conditions? New paper published on Physica A: https://doi.org/10.1016/j.physa.2022.128336

 

April 2022: Our younger lab members Kieran Brian and Oliver Baker, both BSc students in Data Science, had 2 posters accepted for presentation at https://htw2022.stemm.ai ! Well done!

November 2021: New pre-print co-led by our student Simmi Marina Joseph together with Salvatore Citraro, Virginia Morini and Giulio Rossetti of KDD Lab, CNR, Italy and University of Pisa:

https://arxiv.org/abs/2110.15269

October 2021: New pre-print led by our student Asra Fatima, in collaboration with Ying Li and Thomas T. Hills:

https://arxiv.org/abs/2110.13710

 

September 2021: New paper out on Scientific Reports, in collaboration with Andreia Sofia Teixeira, Szymon Talaga and Trevor J Swanson: 

https://www.nature.com/articles/s41598-021-98147-w

September 2021: Our lab members Asra Fatima, Simmi Marina Joseph and Martyna Wozniak had 3 abstracts accepted for presentation at CompCog21, satellite of CCS2021!

May 2021: Oral presentation accepted at Networks 2021, a joint Sunbelt and Netsci conference.

May 2021: Prof. Yoed N. Kenett (Technion, Israel) visited our lab by giving an invited lecture about cognitive network science.

 

March 2021: A new pre-print out: Cognitive network science investigating emotional perceptions of COVID-19 vaccines on social media. ArXiv version here.

December 2020: We are live, hello world!