Complexity and Cognition

The search for emotions, creativity and fairness in language

Emotions are central to human experience, creativity, and behavior. They are crucial for organizing meaning and reasoning about the world we live in. They are ubiquitous and everyday, yet complex and nuanced. In this talk, I will describe our work on the search for emotions in language -- by humans (through data annotation projects) and by machines (in automatic emotion and sentiment analysis systems). I will outline ways in which emotions can be represented, challenges in obtaining reliable annotations, and approaches that lead to high-quality annotations and useful sentiment analysis systems. I will discuss wide-ranging applications of emotion detection in natural language processing, psychology, social sciences, digital humanities, and computational creativity. Along the way, I will discuss various ethical considerations involved in emotion recognition and sentiment analysis — the often unsaid assumptions and the real-world implications of our choices.

Disentangling conceptual concreteness and categorical specificity

When talking about the phenomenon of abstraction we may refer to the distinction between concrete and abstract concepts ("banana" vs "belief") or to the difference between conceptual categories with different degrees of inclusiveness ("animal" vs "sheep").

In this talk, I will show the relation between these two variables, which I call concreteness and specificity, and their importance for language processing in the human and in the artificial minds.

The generalized total entropy fit index: How to verify the fit of hierarchical structures in networks.

Fit indices are essential in psychometrics because they provide a way to evaluate how well a statistical model fits the empirical data. In psychometric research, statistical models are commonly used to represent the relationships between different psychological variables, such as personality traits or cognitive abilities, and how these variables are organized. Model fit can help researchers understand the underlying structure of the variables and make predictions about their behavior. For example, a good fit index can help researchers determine whether a particular model (e.g., five general factors of personality) provides a good explanation of the data (e.g., collected using a personality questionnaire), or whether the model needs to be revised in order to better capture the relationships between the variables (e.g., three general factors instead of five). Fit indices are, therefore, an essential tool in psychometric research, as they allow researchers to evaluate the quality of their models and ensure that they are accurately representing the data. In this talk, I will introduce the generalized total entropy fit index, a new fit index for hierarchical structures in network psychometrics.

This satellite will fit within a full day. In order to keep reasonable attention spans and include as many contributed talks as possible within the above time limit, both invited talks and contributed talks will be shorter than in mainstream in-person satellites.

Contributed talks will last 10 mins + 5 mins discussion (Q&A) each, whereas invited talks will last for 20 mins + Q/A (10 mins) each. There will be also a poster session (organised via Gather Town = 45 mins) and a tutorial session on cognitive network science guided by the Scientific Committee (45 mins).

We also plan to have at least two coffee breaks and organize activities in two blocks, one in the CET morning and one in the CET afternoon, in order to overlap with both the US and the Asian/Australian time zones.

The call for contributed talks is currently CLOSED (but you can still register to the event). Relevant topics include, but are not limited to:

• Network psychometrics and cognitive modelling;

• Complex systems and cognition;

• Social media inquiry under the lens of cognitive science;

• Artificial intelligence, machine learning and psychological data;

• Network models of the human brain and/or mind;

• Big Data, personality traits and human dynamics;

• System thinking, clinical populations and mental health;

• Creativity, fluid intelligence and cognitive skills as complex systems;

• Personality traits and complex networks.

Satellite registration and potential contributions are managed through a Google Form (see bottom page). The Committee will sift abstracts. Each Committee member will vote for acceptance or rejection of each potential contribution.

Only contributions unanimously accepted by the Committee will be accepted for presentation. The Main Organiser will not vote for acceptance but will gather and coordinate votes and then notify acceptance/rejection. Authors of rejected submissions might still produce a poster. Alternatively, authors can indicate whether they prefer to present a poster or a contributed talk.

Note: Please send a 1-page abstract including a short narrative (between 150 and 300 words), a figure (required), and a few key references (optional).