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检索条件"丛书名=Lecture Notes in Computer Science"

共 300228 条记录，以下是161-170 订阅

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Don't Let MEV Slip: The Costs of Swapping on the Uniswap Protocol 28th

Don't Let MEV Slip: The Costs of Swapping on the Uniswap Pro...

引用

28th International Conference on Financial Cryptography and Data Security

作者： Adams, Austin Chan, Benjamin Y. Markovich, Sarit Wan, Xin Uniswap Labs New York NY USA Cornell Tech New York NY 10044 USA Northwestern Univ Evanston IL USA

ISBN: (纸本)9783031786754;9783031786761

We present the first in-depth empirical characterization of the costs of trading on a decentralized exchange (DEX). Using quoted prices from the Uniswap Labs interface for two pools-USDC-ETH (5bps) and PEPE-ETH (30bps)-we evaluate the efficiency of trading on DEXs. Our main tool is slippage-the difference between the realized execution price of a trade, and its quoted price-which we breakdown into its benign and adversarial components. We also present an alternative way to quantify and identify slippage due to adversarial reordering of transactions, which we call reordering slippage, that does not require quoted prices or mempool data to calculate. We find that the composition of transaction costs varies tremendously with the trade's characteristics. Specifically, while for small swaps, gas costs dominate costs, for large swaps price-impact and slippage account for the majority of it. Moreover, when trading PEPE, a popular 'memecoin', the probability of adversarial slippage is about 80% higher than when trading a mature asset like USDC. Overall, our results provide preliminary evidence that DEXs offer a compelling trust-less alternative to centralized exchanges for trading digital assets.

关键词： Decentralized finance

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Identifying Cyberbullying Roles in Social Media 16th

Identifying Cyberbullying Roles in Social Media

引用

16th International Conference on Social Networks Analysis and Mining

作者： Sandoval, Manuel Abuhamad, Mohammed Furman, Patrick Nazari, Mujtaba Hall, Deborah L. Silva, Yasin N. Loyola Chicago Univ Chicago IL 60660 USA Arizona State Univ Glendale AZ 85306 USA

ISBN: (纸本)9783031785474;9783031785481

Social media has revolutionized communication, allowing people worldwide to connect and interact instantly. However, it has also led to increases in cyberbullying, which poses a significant threat to children and adolescents globally, affecting their mental health and well-being. It is critical to accurately detect the roles of individuals involved in cyberbullying incidents to effectively address the issue on a large scale. This study explores the use of machine learning models to detect the roles involved in cyberbullying interactions. After examining the AMiCA dataset and addressing class imbalance issues, we evaluate the performance of various models built with four underlying LLMs (i.e. BERT, RoBERTa, T5, and GPT-2) for role detection. Our analysis shows that oversampling techniques help improve model performance. The best model, a fine-tuned RoBERTa using oversampled data, achieved an overall F1 score of 83.5%, increasing to 89.3% after applying a prediction threshold. The top-2 F1 score without thresholding was 95.7%. Our method outperforms previously proposed models. After investigating the per-class model performance and confidence scores, we show that the models perform well in classes with more samples and less contextual confusion (e.g. Bystander Other), but struggle with classes with fewer samples (e.g. Bystander Assistant) and more contextual ambiguity (e.g. Harasser and Victim). This work highlights current strengths and limitations in the development of accurate models with limited data and complex scenarios.

关键词： cyberbullying role detection social media LLM

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Exploring Collaborative Interactive Digital Narrative Creation in Higher Education Through Narrative Analysis: A Case Study on COVID-19 Storytelling 17th

Exploring Collaborative Interactive Digital Narrative Creati...

引用

17th International Conference on Interactive Digital Storytelling

作者： Petousi, Dimitra Katifori, Akrivi Boile, Maria Sifaki, Eirini Athena Res & Innovat Ctr Maroussi 15125 Greece Univ Thessaly Dept Language & Intercultural Studies Volos 38221 Greece

ISBN: (纸本)9783031784491;9783031784507

This paper explores collaborative IDN creation as a pedagogical approach in higher education. Drawing on theories of constructivism and social learning, we believe that collaborative IDN creation can foster knowledge-building and diverse perspectives. To investigate this approach, we conducted a study involving a class of college students tasked with creating IDNs about the COVID-19 pandemic. As the first step, we analyze the theme, interactivity, agency, and other elements of their IDNs, to understand the potential benefits and challenges of this method. Students demonstrated a diverse range of storytelling approaches, incorporating a range of elements and themes. Future work will focus on in-depth interviews to gain insight into their thought process, motivations around design decisions, sense of co-creation and perceived learning outcomes.

关键词： Collaborative Creation Digital Storytelling Social Learning Higher Education

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Building Visual Novels with Social Simulation and Storylets 17th

Building Visual Novels with Social Simulation and Storylets

引用

17th International Conference on Interactive Digital Storytelling

作者： Johnson-Bey, Shi Liao, Kira Shields, Samuel Hwang, Daeun Wardrip-Fruin, Noah Mateas, Michael Melcer, Edward Univ Calif Santa Cruz Santa Cruz CA 95064 USA

ISBN: (纸本)9783031784491;9783031784507

Simulationist interactive narrative systems allow game makers to craft reactive stories driven by simulated characters and their social dynamics. These systems produce narrative experiences that feel more emergent but may lack a coherent plot structure. We explored how to combine the emergent possibilities of social simulation with a procedural narrative system that affords writers strong authorial control over the plot. We did this by developing a Unity extension called Anansi that helps people create social simulation-driven visual novels. It enables users to inject simulation data into their story dialogue using logical queries and parameterized storylets written using Ink. The paper describes an overview of our extension and how we empower writers to drive narrative progression using cascading social effects from player choices.

关键词： Storylets Tools Social Simulation Unity Visual Novel

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Network Analysis of Indian Corporate Interlocks Patterns, Players and Sectors 16th

Network Analysis of Indian Corporate Interlocks Patterns, Pl...

引用

16th International Conference on Social Networks Analysis and Mining

作者： Gupta, Yayati Seth, Aaditeshwar Sukhija, Sanatan Mahindra Univ Hyderabad India Indian Inst Technol Delhi Delhi India

ISBN: (纸本)9783031785535;9783031785542

Corporate interlock networks have received significant attention, especially in developed economies such as the USA, Japan, Germany, etc. However, their significance in developing Asian countries, where corporate governance regulations are relatively lax, remains crucial. Especially concerning India, its intricate history and diverse heritage contribute to a distinctive and intricate corporate environment. While numerous studies have attempted to address this, they often suffer from limited data scope, typically focusing on a few hundred firms. In this study, we analyze a bipartite network comprising 4601 Indian firms and 25569 directors. Our analysis explores the cohesion among key actors and fragmentation of the market across sectors. We observed that companies with large board sizes tend to form an elite structure, maintaining dense connections among themselves. In contrast, we did not observe such an elite structure among the directors. The study also reveals distinct characteristics of the manufacturing, agriculture, and power sectors within this intricate network.

关键词： Corporate interlock network Bipartite network analysis Interlocking directorates Centrality Community detection Assortativity

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Path2Vec: Representation Learning for Node Sequences Based on Contrastive Learning 16th

Path2Vec: Representation Learning for Node Sequences Based o...

引用

16th International Conference on Social Networks Analysis and Mining

作者： Fushimi, Takayasu Kawasaki, Yuki Tokyo Univ Technol Tokyo Japan

ISBN: (纸本)9783031785535;9783031785542

We often deal with sequences of nodes on graphs, such as routes from departure points to destinations in road networks, and information diffusion routes from information sources in SNS. While there has been much research on nodes and edges in graph machine learning, and many methods for embedding them in vector spaces have been proposed, there is little research on node sequences (path), and a method for embedding node sequences in vector space has not been established. In this study, for node sequences, we propose a novel method for embedding paths in a vector space by considering the nature and appearance order of nodes. Our method learns the vectors so that paths consisting of nodes with similar characteristics or consisting of the same nodes become similar vectors, whereas consisting of nodes with different properties or distant nodes become dissimilar vectors. The proposed method uses the framework of Contrastive Learning, which is a type of self-supervised learning. Specifically, a similar node sequence is generated by fixing the starting point, intermediate points, and ending point, and data-augmenting the path based on a random walk. Then, we nonlinearly project the encoded vectors considering the node vectors and the order of appearance, and learn various parameters so that the similarity of the embedding vectors of node sequences generated from the same starting point and ending point is high. Through evaluation experiments using actual road network data, we confirm that the desired vector can be obtained.

关键词： Embedding Node Sequences Contrastive Learning Data Augmentation Random Walk

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A New Approach to Estimating Bitcoin Production Cost 9th

A New Approach to Estimating Bitcoin Production Cost

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28th International Conference on Financial Cryptography and Data Security

作者： Yamamoto, Go NTT Digital Inc Tokyo Japan

ISBN: (纸本)9783031692307;9783031692314

Estimating Bitcoin production cost is a common concern for economists, financial engineers, environmental activists, investors, and regulators. The costs affect the robustness of the Bitcoin ecosystem, the sustainability of its energy consumption, and ultimately, the value of its assets. The existing estimation approach relies on estimating power consumption by analyzing the performance of mining hardware available in the market. This paper proposes a new approach to estimating Bitcoin production cost, based on a behavioral model of miners instead of analyzing energy costs by surveying mining hardware profiles. We apply a theoretical model that derives the rational hash rate from a miner's risk tolerance to infer the production cost solely from changes in the Bitcoin price and the mining difficulty parameter. We present methods to generate a time series of estimated production costs using actual Bitcoin prices and difficulty parameters. The results show that the estimated production costs, using only Bitcoin prices and difficulty parameters, closely track the energy costs estimated from mining hardware profiles. This suggests that most miners behave rationally, as the model assumes, and that we have obtained an alternative method to estimate the cost of Bitcoin production.

关键词： Cost estimating

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Prescient Perspectives on Football Tactics: A Case with Liverpool FC, Corners and AI 16th

Prescient Perspectives on Football Tactics: A Case with Live...

引用

16th International Conference on Social Networks Analysis and Mining

作者： Roccetti, Marco Tenace, Marco Cappiello, Giuseppe Univ Bologna Dept Comp Sci & Engn Bologna Italy Univ Bologna Dept Management Bologna Italy

ISBN: (纸本)9783031785535;9783031785542

Prescient (not prescientific) ideas are those that challenge the assumptions that predominate a given field and that typify beforehand the future of that domain. In this short communication, we question how much we are willing to believe that predictive Artificial Intelligence is already able to suggest good prescient ideas on football, for example by hinting the tactical adjustments needed to shoot corner kicks that finally end in goals. We have conducted statistical Chi-squared tests that show that the Liverpool Football Club, in the Premier League seasons 2021/22, 2022/23 and 2023/24, has reached a higher potential for goals from corners with respect to the previous seasons 2016/17, 2017/18 and 2018/19, only in the attacking phase of play (scored goals), but not in the defensive one (conceded goals). This despite a multi-year collaboration between Liverpool FC and authors of [1] on AI, reportedly begun during the season 2020/21. Moreover, no statistically significant difference was found, with another series of Chi-squared tests, between the goals scored/conceded from corner kicks by Liverpool FC and those scored/conceded, in the seasons 2021-24, by Arsenal FC and Manchester City FC. Our study suggests preliminary evidence against the belief that AI is ready to prompt prescient ideas in a dynamic domain, characterized by many multi-agent interactions, like football. Limitations to these results come from the uncertainty on the real nature of the collaboration between Liverpool FC and AI on corner kicks, as discussed at length in the paper.

关键词： Football data analysis Artificial intelligence Prescient ideas

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A Model of Net Flaming Caused by News Propagation in Online Social Networks 16th

A Model of Net Flaming Caused by News Propagation in Online ...

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16th International Conference on Social Networks Analysis and Mining

作者： Tada, Harumasa Murata, Masayuki Aida, Masaki Kyoto Univ Educ Kyoto Kyoto 6128522 Japan Osaka Univ Suita Osaka 5650871 Japan Tokyo Metropolitan Univ Hino Tokyo 1910065 Japan

ISBN: (纸本)9783031785375;9783031785382

Net flaming that occurs on Online Social Networks (OSNs) has become a serious problem. Net flaming occurs when some news is spread on OSNs and users react strongly to it. In OSNs, however, net flaming can occur even though there is nothing particularly wrong with the news itself that is spread. In this paper, we use a network oscillation model to analyze user dynamics caused by news propagation in OSNs, and show that net flaming may be caused by user comments added to the news during the propagation process. Based on these observations, we discuss countermeasures to suppress net flaming.

关键词： Online flaming Oscillation model Spectral graph theory Laplacian matrix

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Improving the Accuracy of Community Detection in Social Network Through a Hybrid Method 16th

Improving the Accuracy of Community Detection in Social Netw...

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16th International Conference on Social Networks Analysis and Mining

作者： Nooribakhsh, Mahsa Fernandez-Diego, Marta Gonzalez-Ladron-De-Guevara, Fernando Mollamotalebi, Mahdi Univ Politecn Valencia Inst Univ Mixto Tecnol Informat Camino Vera S-N Valencia 46022 Spain Islam Azad Univ Dept Comp & Informat Technol Engn Qazvin Branch Qazvin Iran

ISBN: (纸本)9783031785375;9783031785382

The inherent complexity of social networks in terms of topological properties requires sophisticated methodologies to detect communities or clusters. Community detection in social networks is essential for understanding organizational structures and patterns in complex interconnected systems. Traditional methods face challenges in handling the scale and complexity of modern social networks, such as local optima trapping and slow convergence. This paper proposes a hybrid method to improve the accuracy of community detection, leveraging stacked auto-encoder (SAE) for dimensionality reduction and the Shuffled Frog Leaping (SFLA) as memetic algorithm for enhanced optimization alongside k-means clustering. The proposed method constructs a hybrid similarity matrix combining structural information and community-related features, followed by SAE to reduce dimensionality and facilitate efficient processing of high-dimensional data. SFLA optimizes the k-means clustering process, introducing adaptability and diversity to exploration of the solution space. Experimental results indicated its superior performance in terms of normalized mutual information (NMI) and modularity compared to existing approaches.

关键词： community detection social networks stacked auto-encoder shuffled frog leaping algorithm

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