Dear students,
tomorrow we will have a two-slot seminar featuring
- Fabio Morea, Head of the Sustainability Office at Area Science Park Trieste and PhD candidate in Applied Data Science and Artificial Intelligence at the University of Trieste;
- Mingmeng Geng, PhD candidate at the International School for Advanced Studies (Scuola Internazionale Superiore di Studi Avanzati, SISSA), Trieste.
The relevant seminar for you is the one by Fabio but Mingmeng presents a nice topic on scientific production data (sometimes we treated scientific collaboration network and this is a related topic).
The seminar will be held in Room 1C of the H3 building at 1:30pm. Other phd students and postdocs will also attend them.
Here the abstracts of both seminars.
Speaker: Fabio Morea
Provisional Title: Navigating Networks and Communities with Data Science
Provisional Abstract: Networks are anywhere around us, in social, business or academic contexts. Whenever individuals, organizations, or companies seek to connect with others, whether to compete or collaborate, a network is established, and evolves over time, as partnerships shift, and new leaders emerge.
An increasing number of complex and large datasets have become available in recent years providing a great opportunity to identify networks that extend over long periods of time and involve thousands of actors and connections.
Over the past 20 years, researchers have developed a theoretical framework and a large set of tools to explore networks’ structure, however, some aspects are still open.
This seminar, titled 'Navigating Networks and Communities with Data Science', provides a general overview of the topic, a novel framework for unsupervised community detection. Examples will be taken from a comprehensive dataset provided by the European Commission, which describes companies and research organizations that participated in the Horizon Framework Programmes over a period of 15 years.
The seminar is based on the research conducted by the Author within the frame of a PhD in Applied Data Science and Artificial Intelligence (www.adsai.it) under the supervision of prof. Domenico De Stefano.
Speaker: Mingmeng Geng
Title: Is ChatGPT Transforming Academics' Writing Style?
Abstract: Based on one million arXiv papers submitted from May 2018 to January 2024, we assess the textual density of ChatGPT's writing style in their abstracts by means of a statistical analysis of word frequency changes. Our model is calibrated and validated on a mixture of real abstracts and ChatGPT-modified abstracts (simulated data) after a careful noise analysis. We find that ChatGPT is having an increasing impact on arXiv abstracts, especially in the field of computer science, where the fraction of ChatGPT-revised abstracts is estimated to be approximately 35%, if we take the output of one of the simplest prompts, "revise the following sentences", as a baseline. We conclude with an analysis of both positive and negative aspects of the penetration of ChatGPT into academics' writing style.