publications | Lucio La Cava, Ph.D.

2025

Exploring LLMs’ Ability to Spontaneously and Conditionally Modify Moral Expressions through Text Manipulation

Candida Maria Greco, Lucio La Cava, Lorenzo Zangari, and 1 more author

To appear in Proceedings of the ACL 2025 (Main Conference), May 2025

@article{Greco2025morality,
  title = {Exploring LLMs’ Ability to Spontaneously and Conditionally Modify Moral Expressions through Text Manipulation},
  journal = {To appear in Proceedings of the ACL 2025 (Main Conference)},
  author = {Greco, Candida Maria and La Cava, Lucio and Zangari, Lorenzo and Tagarelli, Andrea},
  year = {2025},
  month = may,
  bibtex_show = true,
  selected = true
}

OpenTuringBench: An Open-Model-based Benchmark and Framework for Machine-Generated Text Detection and Attribution

Lucio La Cava, and Andrea Tagarelli

arXiv preprint arXiv:2504.11369, Apr 2025

arXiv Bib

@article{LaCava2025otb,
  title = {OpenTuringBench: An Open-Model-based Benchmark and Framework for Machine-Generated Text Detection and Attribution},
  journal = {arXiv preprint arXiv:2504.11369},
  author = {La Cava, Lucio and Tagarelli, Andrea},
  year = {2025},
  month = apr,
  bibtex_show = true,
  selected = true
}

Unveiling User Dynamics in the Evolving Social Debate on Climate Crisis During the Conferences of the Parties

Liliana Martirano, Lucio La Cava, and Andrea Tagarelli

Just accepted with Pervasive and Mobile Computing, May 2025

Bib

@article{Martirano2025pmcn,
  title = {Unveiling User Dynamics in the Evolving Social Debate on Climate Crisis During the Conferences of the Parties},
  author = {Martirano, Liliana and La Cava, Lucio and Tagarelli, Andrea},
  journal = {Just accepted with Pervasive and Mobile Computing},
  month = may,
  year = {2025},
  bibtex_show = true,
  selected = false
}

Characterizing Swing Voters in Online Social Media: The Case of the 2022 Italian Elections

Alessia Antelmi, Lucio La Cava, and Arianna Pera

Just accepted with Social Network Analysis and Mining, Mar 2025

arXiv Bib

@article{Antelmi2024swingvoters,
  title = {Characterizing Swing Voters in Online Social Media: The Case of the 2022 Italian Elections},
  author = {Antelmi, Alessia and La Cava, Lucio and Pera, Arianna},
  journal = {Just accepted with Social Network Analysis and Mining},
  month = mar,
  year = {2025},
  bibtex_show = true,
  selected = true
}

Heuristic-Informed Mixture of Experts for Link Prediction in Multilayer Networks

Lucio La Cava, Domenico Mandaglio, Lorenzo Zangari, and 1 more author

arXiv preprint arXiv:2501.17557, Jan 2025

arXiv Bib

@article{lacava2025mlmoe,
  title = {Heuristic-Informed Mixture of Experts for Link Prediction in Multilayer Networks},
  author = {La Cava, Lucio and Mandaglio, Domenico and Zangari, Lorenzo and Tagarelli, Andrea},
  journal = {arXiv preprint arXiv:2501.17557},
  year = {2025},
  month = jan,
  bibtex_show = true,
  selected = true
}

Open Models, Closed Minds? On Agents Capabilities in Mimicking Human Personalities through Open Large Language Models

Lucio La Cava, and Andrea Tagarelli

Proceedings of the AAAI Conference on Artificial Intelligence, Apr 2025

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The emergence of unveiling human-like behaviors in Large Language Models (LLMs) has led to a closer connection between NLP and human psychology. However, research on the personalities exhibited by LLMs has largely been confined to limited investigations using individual psychological tests, primarily focusing on a small number of commercially licensed LLMs. This approach overlooks the extensive use and significant advancements observed in open-source LLMs. This work aims to address both the above limitations by conducting an in-depth investigation of a significant body of 12 LLM Agents based on the most representative Open models, through the two most well-known psychological assessment tests, namely Myers-Briggs Type Indicator (MBTI) and Big Five Inventory (BFI). Our approach involves evaluating the intrinsic personality traits of LLM agents and determining the extent to which these agents can mimic human personalities when conditioned by specific personalities and roles. Our findings unveil that (i) each LLM agent showcases distinct human personalities; (ii) personality-conditioned prompting produces varying effects on the agents, with only few successfully mirroring the imposed personality, while most of them being “closed-minded’’ (i.e., they retain their intrinsic traits); and (iii) combining role and personality conditioning can enhance the agents’ ability to mimic human personalities. Our work represents a step up in understanding the dense relationship between NLP and human psychology through the lens of LLMs.
@article{LaCava2024agentspersonalities, title = {Open Models, Closed Minds? On Agents Capabilities in Mimicking Human Personalities through Open Large Language Models}, volume = {39}, doi = {10.1609/aaai.v39i2.32125}, number = {2}, journal = {Proceedings of the AAAI Conference on Artificial Intelligence}, author = {La Cava, Lucio and Tagarelli, Andrea}, year = {2025}, month = apr, pages = {1355-1363}, bibtex_show = true, selected = true }

Visually Wired NFTs: Exploring the Role of Inspiration in Non-Fungible Tokens

Lucio La Cava, Davide Costa, and Andrea Tagarelli

ACM Trans. Web, Jan 2025

Bib HTML

@article{LaCava2025visually,
  author = {La Cava, Lucio and Costa, Davide and Tagarelli, Andrea},
  title = {Visually Wired NFTs: Exploring the Role of Inspiration in Non-Fungible Tokens},
  year = {2025},
  publisher = {Association for Computing Machinery},
  address = {New York, NY, USA},
  issn = {1559-1131},
  doi = {10.1145/3703411},
  journal = {ACM Trans. Web},
  month = jan,
  bibtex_show = true
}

2024

Talking the Talk Does Not Entail Walking the Walk: On the Limits of Large Language Models in Lexical Entailment Recognition

Candida Maria Greco, Lucio La Cava, and Andrea Tagarelli

In Findings of the Association for Computational Linguistics: EMNLP 2024, Nov 2024

Bib HTML

@inproceedings{greco-etal-2024-talking,
  title = {Talking the Talk Does Not Entail Walking the Walk: On the Limits of Large Language Models in Lexical Entailment Recognition},
  author = {Greco, Candida Maria and La Cava, Lucio and Tagarelli, Andrea},
  booktitle = {Findings of the Association for Computational Linguistics: EMNLP 2024},
  month = nov,
  year = {2024},
  address = {Miami, Florida, USA},
  publisher = {Association for Computational Linguistics},
  doi = {10.18653/v1/2024.findings-emnlp.881},
  pages = {14991--15011},
  bibtex_show = true,
  selected = true
}

Is Contrasting All You Need? Contrastive Learning for the Detection and Attribution of AI-generated Text

Lucio La Cava, Davide Costa, and Andrea Tagarelli

In ECAI 2024 - 27th European Conference on Artificial Intelligence, 19-24 October 2024, Santiago de Compostela, Spain, Oct 2024

Bib HTML

@inproceedings{LaCava2024AIdetection,
  author = {La Cava, Lucio and Costa, Davide and Tagarelli, Andrea},
  title = {Is Contrasting All You Need? Contrastive Learning for the Detection
                    and Attribution of AI-generated Text},
  booktitle = {{ECAI} 2024 - 27th European Conference on Artificial Intelligence,
                    19-24 October 2024, Santiago de Compostela, Spain},
  series = {Frontiers in Artificial Intelligence and Applications},
  volume = {392},
  pages = {3179--3186},
  publisher = {{IOS} Press},
  month = oct,
  year = {2024},
  doi = {10.3233/FAIA240862},
  bibtex_show = true,
  selected = true
}

Safeguarding Decentralized Social Media: LLM Agents for Automating Community Rule Compliance

Lucio La Cava, and Andrea Tagarelli

arXiv preprint arXiv:2409.08963, Sep 2024

arXiv Bib

@article{LaCava2024safeguarding,
  title = {Safeguarding Decentralized Social Media: LLM Agents for Automating Community Rule Compliance},
  author = {La Cava, Lucio and Tagarelli, Andrea},
  journal = {arXiv preprint arXiv:2409.08963},
  month = sep,
  year = {2024},
  bibtex_show = true,
  selected = true
}

An Exploration of Decentralized Moderation on Mastodon

Carlo Alberto Bono, Lucio La Cava, Luca Luceri, and 1 more author

In Proceedings of the 16th ACM Web Science Conference, May 2024

Bib HTML

@inproceedings{Bono2024decentralizedmoderation,
  author = {Bono, Carlo Alberto and La Cava, Lucio and Luceri, Luca and Pierri, Francesco},
  title = {An Exploration of Decentralized Moderation on Mastodon},
  month = may,
  year = {2024},
  isbn = {9798400703348},
  publisher = {Association for Computing Machinery},
  address = {New York, NY, USA},
  doi = {10.1145/3614419.3644016},
  booktitle = {Proceedings of the 16th ACM Web Science Conference},
  pages = {53–58},
  numpages = {6},
  series = {WEBSCI '24},
  bibtex_show = true
}

Polarization in Decentralized Online Social Networks

Lucio La Cava, Domenico Mandaglio, and Andrea Tagarelli

In Proceedings of the 16th ACM Web Science Conference, May 2024

Bib HTML

@inproceedings{LaCava2024polarization,
  author = {{La Cava}, Lucio and Mandaglio, Domenico and Tagarelli, Andrea},
  title = {Polarization in Decentralized Online Social Networks},
  month = may,
  year = {2024},
  doi = {10.1145/3614419.3644013},
  booktitle = {Proceedings of the 16th ACM Web Science Conference},
  series = {WebSci '24},
  bibtex_show = true
}

2023

Drivers of social influence in the Twitter migration to Mastodon

Lucio La Cava, Luca Maria Aiello, and Andrea Tagarelli

Scientific Reports, Dec 2023

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The migration of Twitter users to Mastodon following Elon Musk’s acquisition presents a unique opportunity to study collective behavior and gain insights into the drivers of coordinated behavior in online media. We analyzed the social network and the public conversations of about 75,000 migrated users and observed that the temporal trace of their migrations is compatible with a phenomenon of social influence, as described by a compartmental epidemic model of information diffusion. Drawing from prior research on behavioral change, we delved into the factors that account for variations of the effectiveness of the influence process across different Twitter communities. Communities in which the influence process unfolded more rapidly exhibit lower density of social connections, higher levels of signaled commitment to migrating, and more emphasis on shared identity and exchange of factual knowledge in the community discussion. These factors account collectively for 57% of the variance in the observed data. Our results highlight the joint importance of network structure, commitment, and psycho-linguistic aspects of social interactions in characterizing grassroots collective action, and contribute to deepen our understanding of the mechanisms that drive processes of behavior change of online groups.
@article{LaCava2023SciRep, author = {La Cava, Lucio and Aiello, Luca Maria and Tagarelli, Andrea}, date = {2023/12/07}, doi = {10.1038/s41598-023-48200-7}, id = {Cava2023}, isbn = {2045-2322}, journal = {Scientific Reports}, number = {1}, pages = {21626}, title = {Drivers of social influence in the Twitter migration to Mastodon}, volume = {13}, month = dec, year = {2023}, altmetric = true, dimensions = true, selected = true, bibtex_show = true }
Unraveling the NFT economy: A comprehensive collection of Non-Fungible Token transactions and metadata

Davide Costa, Lucio La Cava, and Andrea Tagarelli

Data in Brief, Nov 2023

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Non-Fungible Tokens (NFTs) have emerged as the most representative application of blockchain technology in recent years, fostering the development of the Web3. Nonetheless, while the interest in NFTs rapidly boomed, creating unprecedented fervour in traders and creators, the demand for highly representative and up-to-date data to shed light on such an intriguing yet complex domain mostly remained unmet. To pursue this objective, we introduce a large collection of NFT transactions and associated metadata that correspond to trading operations between 2021 and 2023. Our developed dataset is the most extensive and representative in the NFT landscape to date, as it contains more than 70 M transactions performed by more than 6 M users across 36.3 M NFTs and 281 K collections. Moreover, this dataset boasts a wealth of metadata, including encoded textual descriptions and multimedia content, thus being suitable for a plethora of tasks relevant to database systems, AI, data science, Web and network science fields. This dataset represents a unique resource for researchers and industry practitioners to delve into the inner workings of NFTs through a multitude of perspectives, paving the way for unprecedented opportunities across multiple research fields.
@article{Costa2023DiB, title = {Unraveling the NFT economy: A comprehensive collection of Non-Fungible Token transactions and metadata}, journal = {Data in Brief}, volume = {51}, pages = {109749}, month = nov, year = {2023}, issn = {2352-3409}, doi = {https://doi.org/10.1016/j.dib.2023.109749}, author = {Costa, Davide and {La Cava}, Lucio and Tagarelli, Andrea}, keywords = {Web3, Blockchain, Cryptocurrencies}, bibtex_show = true, selected = false }

Evolution of the Social Debate on Climate Crisis: Insights from Twitter During the Conferences of the Parties

Liliana Martirano, Lucio La Cava, and Andrea Tagarelli

In 2023 International Conference on Information and Communication Technologies for Disaster Management (ICT-DM), Nov 2023

Bib

@inproceedings{ICTDM2023,
  author = {Martirano, Liliana and La Cava, Lucio and Tagarelli, Andrea},
  booktitle = {2023 International Conference on Information and Communication Technologies for Disaster Management (ICT-DM)},
  title = {Evolution of the Social Debate on Climate Crisis: Insights from Twitter During the Conferences of the Parties},
  year = {2023},
  volume = {},
  number = {},
  pages = {1-6},
  doi = {10.1109/ICT-DM58371.2023.10286927},
  bibtex_show = true
}

SONAR: Web-Based Tool for Multimodal Exploration of Non-Fungible Token Inspiration Networks

Lucio La Cava, Davide Costa, and Andrea Tagarelli

In Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, Nov 2023

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In this work, we present SONAR, a web-based tool for multimodal exploration of Non-Fungible Token (NFT) inspiration networks. SONAR is conceived to support both creators and traders in the emerging Web3 by providing an interactive visualization of the inspiration-driven connections between NFTs, at both individual level and collection level. SONAR can hence be useful to identify new investment opportunities as well as anomalous inspirations. To demonstrate SONAR’s capabilities, we present an application to the largest and most representative dataset concerning the NFT landscape to date, showing how our proposed tool can scale and ensure high-level user experience up to millions of edges.
@inproceedings{LaCava2023SIGIR, author = {La Cava, Lucio and Costa, Davide and Tagarelli, Andrea}, title = {SONAR: Web-Based Tool for Multimodal Exploration of Non-Fungible Token Inspiration Networks}, year = {2023}, isbn = {9781450394086}, publisher = {Association for Computing Machinery}, address = {New York, NY, USA}, doi = {10.1145/3539618.3591821}, booktitle = {Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval}, pages = {3200–3204}, numpages = {5}, keywords = {blockchain, web3, learning from nfts, non-fungible tokens}, location = {<conf-loc>, <city>Taipei</city>, <country>Taiwan</country>, </conf-loc>}, series = {SIGIR '23}, bibtex_show = true }
Show Me Your NFT and I Tell You How It Will Perform: Multimodal Representation Learning for NFT Selling Price Prediction

Davide Costa, Lucio La Cava, and Andrea Tagarelli

In Proceedings of the ACM Web Conference 2023, Nov 2023

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Non-Fungible Tokens (NFTs) represent deeds of ownership, based on blockchain technologies and smart contracts, of unique crypto assets on digital art forms (e.g., artworks or collectibles). In the spotlight after skyrocketing in 2021, NFTs have attracted the attention of crypto enthusiasts and investors intent on placing promising investments in this profitable market. However, the NFT financial performance prediction has not been widely explored to date. In this work, we address the above problem based on the hypothesis that NFT images and their textual descriptions are essential proxies to predict the NFT selling prices. To this purpose, we propose MERLIN, a novel multimodal deep learning framework designed to train Transformer-based language and visual models, along with graph neural network models, on collections of NFTs’ images and texts. A key aspect in MERLIN is its independence on financial features, as it exploits only the primary data a user interested in NFT trading would like to deal with, i.e., NFT images and textual descriptions. By learning dense representations of such data, a price-category classification task is performed by MERLIN models, which can also be tuned according to user preferences in the inference phase to mimic different risk-return investment profiles. Experimental evaluation on a publicly available dataset has shown that MERLIN models achieve significant performances according to several financial assessment criteria, fostering profitable investments, and also beating baseline machine-learning classifiers based on financial features.
@inproceedings{Costa2023WWW, author = {Costa, Davide and La Cava, Lucio and Tagarelli, Andrea}, title = {Show Me Your NFT and I Tell You How It Will Perform: Multimodal Representation Learning for NFT Selling Price Prediction}, year = {2023}, isbn = {9781450394161}, publisher = {Association for Computing Machinery}, address = {New York, NY, USA}, doi = {10.1145/3543507.3583520}, booktitle = {Proceedings of the ACM Web Conference 2023}, pages = {1875–1885}, numpages = {11}, keywords = {Non-Fungible Tokens, Web3, Blockchain, Learning from NFTs}, location = {Austin, TX, USA}, series = {WWW '23}, bibtex_show = true, selected = false }

2022

When Correlation Clustering Meets Fairness Constraints

Francesco Gullo, Lucio La Cava, Domenico Mandaglio, and 1 more author

In Discovery Science, Nov 2022

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The study of fairness-related aspects in data analysis is an active field of research, which can be leveraged to understand and control specific types of bias in decision-making systems. A major problem in this context is fair clustering, i.e., grouping data objects that are similar according to a common feature space, while avoiding biasing the clusters against or towards particular types of classes or sensitive features. In this work, we focus on a correlation-clustering method we recently introduced, and experimentally assess its performance in a fairness-aware context. We compare it to state-of-the-art fair-clustering approaches, both in terms of classic clustering quality measures and fairness-related aspects. Experimental evidence on public real datasets has shown that our method yields solutions of higher quality than the competing methods according to classic clustering-validation criteria, without neglecting fairness aspects.
@inproceedings{Gullo2022DS, author = {Gullo, Francesco and La Cava, Lucio and Mandaglio, Domenico and Tagarelli, Andrea}, editor = {Pascal, Poncelet and Ienco, Dino}, title = {When Correlation Clustering Meets Fairness Constraints}, booktitle = {Discovery Science}, year = {2022}, publisher = {Springer Nature Switzerland}, address = {Cham}, pages = {302--317}, isbn = {978-3-031-18840-4}, html = https://link.springer.com/chapter/10.1007/978-3-031-18840-4_22, bibtex_show = true }
LawNet-Viz: A Web-Based System to Visually Explore Networks of Law Article References

Lucio La Cava, Andrea Simeri, and Andrea Tagarelli

In Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Nov 2022

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We present LawNet-Viz, a web-based tool for the modeling, analysis and visualization of law reference networks extracted from a statute law corpus. LawNet-Viz is designed to support legal research tasks and help legal professionals as well as laymen visually exploring the article connections built upon the explicit law references detected in the article contents. To demonstrate LawNet-Viz, we show its application to the Italian Civil Code (ICC), which exploits a recent BERT-based model fine-tuned on the ICC. LawNet-Viz is a system prototype that is planned for product development.
@inproceedings{LaCava2022SIGIR, author = {La Cava, Lucio and Simeri, Andrea and Tagarelli, Andrea}, title = {LawNet-Viz: A Web-Based System to Visually Explore Networks of Law Article References}, year = {2022}, isbn = {9781450387323}, publisher = {Association for Computing Machinery}, address = {New York, NY, USA}, doi = {10.1145/3477495.3531668}, booktitle = {Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval}, pages = {3300–3305}, numpages = {6}, keywords = {network analysis and visualization, deep language models, law article citation networks, artificial intelligence and law}, location = {Madrid, Spain}, series = {SIGIR '22}, bibtex_show = true }
Information consumption and boundary spanning in Decentralized Online Social Networks: The case of Mastodon users

Lucio La Cava, Sergio Greco, and Andrea Tagarelli

Online Social Networks and Media, Nov 2022

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Decentralized Online Social Networks (DOSNs) represent a growing trend in the social media landscape, as opposed to the well-known centralized peers, which are often in the spotlight due to privacy concerns and a vision typically focused on monetization through user relationships. By exploiting open-source software, DOSNs allow users to create their own servers, or instances, thus favoring the proliferation of platforms that are independent yet interconnected with each other in a transparent way. Nonetheless, the resulting cooperation model, commonly known as the Fediverse, still represents a world to be fully discovered, since existing studies have mainly focused on a limited number of structural aspects of interest in DOSNs. In this work, we aim to fill a lack of study on user relations and roles in DOSNs, by taking two main actions: understanding the impact of decentralization on how users relate to each other within their membership instance and/or across different instances, and unveiling user roles that can explain two interrelated axes of social behavioral phenomena, namely information consumption and boundary spanning. To this purpose, we build our analysis on user networks from Mastodon, since it represents the most widely used DOSN platform. We believe that the findings drawn from our study on Mastodon users’ roles and information flow can pave a way for further development of fascinating research on DOSNs.
@article{LaCava2022OSNEM, title = {Information consumption and boundary spanning in Decentralized Online Social Networks: The case of Mastodon users}, journal = {Online Social Networks and Media}, volume = {30}, pages = {100220}, year = {2022}, issn = {2468-6964}, doi = {10.1016/j.osnem.2022.100220}, author = {{La Cava}, Lucio and Greco, Sergio and Tagarelli, Andrea}, bibtex_show = true }

Network Analysis of the Information Consumption-Production Dichotomy in Mastodon User Behaviors

Lucio La Cava, Sergio Greco, and Andrea Tagarelli

Proceedings of the International AAAI Conference on Web and Social Media, May 2022

Bib HTML

@article{LaCava2022ICWSM,
  title = {Network Analysis of the Information Consumption-Production Dichotomy in Mastodon User Behaviors},
  volume = {16},
  doi = {10.1609/icwsm.v16i1.19391},
  abstractnote = {Decentralized Online Social Networks (DOSNs) are today an established alternative to the popular centralized counterparts. In this work, we push forward research on user behaviors in a decentralized context, by exploring the dichotomy between information consumption and production. Using the Mastodon user network as a proxy for the Fediverse landscape, we address two main research questions: Do the consumers, resp. producers, identified in one instance exhibit the same behavior consistently while interacting with other instances? and, Are there users who behave as consumers in one instance and simultaneously as producers in other instances, or vice versa? In this respect, our results reveal interesting traits of Mastodon users, yet unveil the emergence for further studies that can embrace other services in the Fediverse.},
  number = {1},
  journal = {Proceedings of the International AAAI Conference on Web and Social Media},
  author = {La Cava, Lucio and Greco, Sergio and Tagarelli, Andrea},
  year = {2022},
  month = may,
  pages = {1378-1382},
  html = https://ojs.aaai.org/index.php/icwsm/article/view/19391,
  bibtex_show = true
}

Discovering the Landscape of Decentralized Online Social Networks through Mastodon

Lucio La Cava, Sergio Greco, and Andrea Tagarelli

May 2022

Bib HTML

@article{LaCava2022SEBD,
  title = {Discovering the Landscape of Decentralized Online Social Networks through Mastodon},
  author = {La Cava, Lucio and Greco, Sergio and Tagarelli, Andrea},
  booktitle = {Proceedings of the 30th Italian Symposium on Advanced Database Systems, SEBD},
  location = {Pisa, Italy},
  year = {2022},
  html = https://ceur-ws.org/vol-3194/paper25.pdf,
  bibtex_show = true
}

2021

Understanding the growth of the Fediverse through the lens of Mastodon

Lucio La Cava, Sergio Greco, and Andrea Tagarelli

Applied Network Science, May 2021

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Open-source, Decentralized Online Social Networks (DOSNs) are emerging as alternatives to the popular yet centralized and profit-driven platforms like Facebook or Twitter. In DOSNs, users can set up their own server, or instance, while they can actually interact with users of other instances. Moreover, by adopting the same communication protocol, DOSNs become part of a massive social network, namely the Fediverse. Mastodon is the most relevant platform in the Fediverse to date, and also the one that has attracted attention from the research community. Existing studies are however limited to an analysis of a relatively outdated sample of Mastodon focusing on few aspects at a user level, while several open questions have not been answered yet, especially at the instance level. In this work, we aim at pushing forward our understanding of the Fediverse by leveraging the primary role of Mastodon therein. Our first contribution is the building of an up-to-date and highly representative dataset of Mastodon. Upon this new data, we have defined a network model over Mastodon instances and exploited it to investigate three major aspects: the structural features of the Mastodon network of instances from a macroscopic as well as a mesoscopic perspective, to unveil the distinguishing traits of the underlying federative mechanism; the backbone of the network, to discover the essential interrelations between the instances; and the growth of Mastodon, to understand how the shape of the instance network has evolved during the last few years, also when broading the scope to account for instances belonging to other platforms. Our extensive analysis of the above aspects has provided a number of findings that reveal distinguishing features of Mastodon and that can be used as a starting point for the discovery of all the DOSN Fediverse.
@article{LaCava2021APNS, author = {La Cava, Lucio and Greco, Sergio and Tagarelli, Andrea}, date = {2021/09/01}, doi = {10.1007/s41109-021-00392-5}, isbn = {2364-8228}, journal = {Applied Network Science}, number = {1}, pages = {64}, title = {Understanding the growth of the Fediverse through the lens of Mastodon}, url = {https://doi.org/10.1007/s41109-021-00392-5}, volume = {6}, year = {2021}, altmetric = true, dimensions = true, selected = true, html = https://link.springer.com/article/10.1007/s41109-021-00392-5, bibtex_show = true }

The Italian Civil Code Network Analysis

Lucio La Cava, Andrea Simeri, and Andrea Tagarelli

In Proceedings of the First International Workshop RELATED - Relations in the Legal Domain Workshop, in conjunction with ICAIL, May 2021

Bib HTML

@inproceedings{LaCava2021RELATED,
  title = {The Italian Civil Code Network Analysis},
  author = {La Cava, Lucio and Simeri, Andrea and Tagarelli, Andrea},
  booktitle = {Proceedings of the First International Workshop RELATED - Relations in the Legal Domain Workshop, in conjunction with ICAIL},
  location = {São Paulo, Brazil},
  year = {2021},
  html = https://ceur-ws.org/vol-2896/related_2021_paper_1.pdf,
  bibtex_show = true
}