Alessia Antelmi

@inproceedings{Antelmi_WebSci_2024,

title = {Deciphering Conversational Networks: Stance Detection via Hypergraphs and LLMs},

author = {Daniele De Vinco and Alessia Antelmi and Carmine Spagnuolo and Luca Maria Aiello},

url = {https://doi.org/10.1145/3630744.3658418},

doi = {10.1145/3630744.3658418},

isbn = {9798400704536},

year  = {2024},

date = {2024-01-01},

booktitle = {Companion Publication of the 16th ACM Web Science Conference},

pages = {3–4},

publisher = {Association for Computing Machinery},

address = {Stuttgart, Germany},

series = {Websci Companion '24},

abstract = {Understanding the structural and linguistic properties of conversational data in social media is crucial for extracting meaningful insights to understand opinion dynamics, (mis-)information spreading, and the evolution of harmful behavior. Current state-of-the-art mathematical frameworks, such as hypergraphs and linguistic tools, such as large language models (LLMs), offer robust methodologies for modeling high-order group interactions and unprecedented capabilities for dealing with natural language-related tasks. In this study, we propose an innovative approach that blends these worlds by abstracting conversational networks via hypergraphs and analyzing their dynamics through LLMs. Our aim is to enhance the stance detection task by incorporating the high-order interactions naturally embedded within a conversation, thereby enriching the contextual understanding of LLMs regarding the intricate human dynamics underlying social media data.},

keywords = {analytics, icsc},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Antelmi_WAW_2024,

title = {HypergraphRepository: A Community-Driven and Interactive Hypernetwork Data Collection},

author = {Alessia Antelmi and Daniele De Vinco and Carmine Spagnuolo},

editor = {Megan Dewar and Bogumił Kamiński and Daniel Kaszyński and Łukasz Kraiński and Paweł Prałat and François Théberge and Małgorzata Wrzosek},

doi = {10.1007/978-3-031-59205-8_11},

isbn = {978-3-031-59205-8},

year  = {2024},

date = {2024-01-01},

booktitle = {Modelling and Mining Networks},

pages = {159–173},

publisher = {Springer Nature Switzerland},

address = {Cham},

abstract = {Hypergraph research has been thriving over the past few years, with a growing interest in a plethora of domains. Despite this remarkable surge, the lack of a comprehensive platform for searching and downloading diverse and well-curated datasets poses a significant obstacle to the continued advancement of the field. This absence hinders the ability of researchers and practitioners to validate and benchmark their hypergraph algorithms and models effectively.},

keywords = {analytics, icsc},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Antelmi_CNA1_2023,

title = {Tell Me Who You Are and I Will Predict Your Vulnerability to Political Persuasion Techniques},

author = {Alessia Antelmi and Luca La Cava and Arianna Pera},

url = {https://iris.unito.it/bitstream/2318/1949370/1/_CNA__23__Personality_vs_propaganda.pdf},

year  = {2023},

date = {2023-01-01},

booktitle = {The 12th International Conference on Complex Networks and their Applications-Book of Abstracts},

abstract = {Given the evolving role of social media in political communication and the strategic use of these platforms by politicians to shape public opinion, research has commonly focused on investigating computational propaganda as a means for automated information diffusion. Focusing on a less explored yet promising line, we aim to assess political persuasion in digital contexts by introducing a computational framework that combines Natural Language Processing and Network Science methods to investigate the linkage between persuasion techniques on social media and personality traits of online political audiences. Our final goal is to enhance public awareness of political tactics and encourage critical thinking in response to the online spread of political information.},

keywords = {analytics, icsc},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Antelmi_CNA_2023,

title = {Finding Hidden Swingers in the 2022 Italian Elections Twitter Discourse},

author = {Alessia Antelmi and Luca La Cava and Arianna Pera},

url = {https://iris.unito.it/bitstream/2318/1949354/1/_CNA__23__TweetYourMind.pdf},

year  = {2023},

date = {2023-01-01},

booktitle = {The 12th International Conference on Complex Networks and their Applications-Book of Abstracts},

abstract = {The volume of the Italian online political discourse on social media has recently increased, but the coverage level does not compare with other Countries such as the US. Nonetheless, researchers focused on studying polarization and homophily with respect to political debates or investigating the role of populism in online engagement. In this research landscape, the analysis of political preference shifts through social media remains to be explored. We aim to bridge this gap by examining the Twitter discourse during the 2022 Italian general elections, with a specific emphasis on political "swingers". In particular, our findings indicate a stable political discourse in Italy, yet they also uncover a growing presence of political swingers willing to shift their support to significantly different factions.},

keywords = {analytics, icsc},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Antelmi_ITADATA_2023,

title = {The SWH-Analytics Framework},

author = {Alessia Antelmi and Massimo Torquati and Daniele Gregori and Francesco Polzella and Gianmarco Spinatelli and Marco Aldinucci},

editor = {Nicola Bena and Beniamino Di Martino and Antonio Maratea and Alessandro Sperduti and Emanuel Di Nardo and Angelo Ciaramella and Raffaele Montella and Claudio A. Ardagna},

url = {https://ceur-ws.org/Vol-3606/paper76.pdf},

year  = {2023},

date = {2023-01-01},

booktitle = {Proceedings of the 2nd Italian Conference on Big Data and Data Science (ITADATA 2023), Naples, Italy, September 11-13, 2023},

volume = {3606},

publisher = {CEUR-WS.org},

series = {CEUR Workshop Proceedings},

abstract = {The Software Heritage (SWH) dataset serves as a vast repository for open-source code, with the ambitious goal of preserving all publicly available open-source projects. Despite being designed to effectively archive project files, its size of nearly 1 petabyte presents challenges in efficiently supporting Big Data MapReduce or AI systems. To address this disparity and enable seamless custom analytics on the SWH dataset, we present the SWH-Analytics (SWHA) architecture. This development environment quickly and transparently runs custom analytic applications on open-source software data preserved over time by SWH.},

keywords = {admire, analytics, icsc},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Antelmi_IC2S2_2023,

title = {Towards Unraveling Developers Communities in Stack Overflow and Reddit},

author = {Alessia Antelmi and Daniele De Vinco and Gennaro Cordasco and Carmine Spagnuolo},

url = {https://openreview.net/forum?id=WP5ZaAFP19},

year  = {2023},

date = {2023-01-01},

booktitle = {International Conference on Computational Social Science 2023},

abstract = {This work investigates the developers' behavior and community formation around the twenty most popular programming languages. We examined two consecutive years of programming-related questions from Stack Overflow and Reddit, performing a longitudinal study on users' posting activity and their high-order interaction patterns abstracted via hypergraphs. Our analysis highlighted crucial differences in how these QA platforms are utilized by their users. In line with previous literature, it emphasized the constant decline of Stack Overflow in favor of more community-friendly platforms, such as Reddit, which has been growing rapidly lately.},

keywords = {analytics, icsc},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Antelmi_TEL4FC_2023,

title = {Engagement in Open Data Workshops: The dark side of remote settings},

author = {Alessia Antelmi},

url = {https://link.springer.com/chapter/10.1007/978-3-031-42134-1_33},

year  = {2023},

date = {2023-01-01},

booktitle = {Methodologies and Intelligent Systems for Technology Enhanced Learning, 12th International Conference},

publisher = {Springer International Publishing},

address = {Cham},

abstract = {The increasing availability of Open Data gives birth to a fertile field for interested stakeholders to create value out of them; however, limited technical expertise and poor awareness are crucial barriers to their exploitation. Because of these reasons, there is an urge for learners to acquire data and information literacy competencies, which are essential for 21st-century skills, and become familiar with available Open Data sources and their potential uses. To promote the dialogue around activities to boost recognition of Open Data and improve users' skills to work with them, we proposed a series of workshops to introduce Italian high school learners to searching for, authoring, and building effective communication based on Open Data. This article describes an ongoing activity and details its organization, reports preliminary results on learners' engagement, and discusses both challenges of the remote setting as well as promising learning outcomes.},

keywords = {analytics, icsc},

pubstate = {published},

tppubtype = {inproceedings}

}