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共 300228 条记录，以下是81-90 订阅

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Online Social Community Neighborhood Formation 16th

Online Social Community Neighborhood Formation

引用

16th International Conference on Social Networks Analysis and Mining

作者： Wang, Jiarui Barnett, George Matloff, Norman Wu, S. Felix Univ Calif Davis Davis CA 95616 USA Natl Cheng Kung Univ Tainan Taiwan

ISBN: (纸本)9783031785405;9783031785412

Online social networks (OSNs) provide community platforms that engage users. The public page is a popular example. These pages are connected through "like" relationships, creating online community networks and neighborhoods. We investigated the pivotal features influencing link formation and neighborhood structuring within the page graph by exploring a series of potential features, both graph-based and content-based. Our methodology combines node similarity and Graph Neural Networks to perform link prediction. We identified the page state label as the single most accurate predictor in link prediction tasks, which also is the most efficient feature with the smallest number of classes. Moreover, we observe that augmenting the page state label feature with the page node degree and page city population features further enhances link prediction accuracy. Page location label shows a strong effect on pages connecting with their neighbors.

关键词： Online social networks Network formation Location Link prediction

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Subset-Optimized BLS Multi-signature with Key Aggregation 28th

Subset-Optimized BLS Multi-signature with Key Aggregation

引用

28th International Conference on Financial Cryptography and Data Security

作者： Baldimtsi, Foteini Chalkias, Konstantinos Kryptos Garillot, Francois Lindstrom, Jonas Riva, Ben Roy, Arnab Sedaghat, Mahdi Sonnino, Alberto Waiwitlikhit, Pun Wang, Joy Mysten Labs Palo Alto CA 94301 USA George Mason Univ Fairfax VA USA Lurk Labs Montreal PQ Canada Katholieke Univ Leuven COSIC Leuven Belgium UCL London England Stanford Univ Stanford CA USA

ISBN: (纸本)9783031786785;9783031786792

We propose a variant of the original Boneh, Drijvers, and Neven (Asiacrypt'18) BLS multi-signature aggregation scheme, which is best suited to applications where the full set of potential signers is fixed and known and any subset I of this group can create a multi-signature over a message m. This setup is very common in proof-of-stake blockchains where if you assume a total of 3f validators, a 2f + 1 majority can sign transactions and/or blocks and is secure against rogue-key attacks without requiring a proof of key possession mechanism. In our scheme, instead of randomizing the aggregated signatures, we have a one-time randomization phase of the public keys: each public key is replaced by a sticky randomized version (for which each participant can still compute the derived private key). The main benefit compared to the original Boneh et al. approach is that since our randomization process happens only once and not per signature we can have significant savings during aggregation and verification without requiring a proof of possession. Specifically, for a subset I of t signers, we save t exponentiations in G(2) at aggregation and t exponentiations in G(1) at verification or vice versa, depending on which BLS mode we prefer: minPK (public keys in G(1)) or minSig (signatures in G(1)). Interestingly, our security proof requires a significant departure from the co-CDH based proof of Boneh et al. When n (size of the universal set of signers) is small, we prove our protocol secure in the Algebraic Group and Random Oracle models based on the hardness of the Discrete Log problem. For larger n, our proof also requires the Random Modular Subset Sum (RMSS) problem.

关键词： BLS multi-signatures signature aggregation blockchain

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Masking the Bias: From Echo Chambers to Large Scale Aspect-Based Sentiment Analysis 16th

Masking the Bias: From Echo Chambers to Large Scale Aspect-B...

引用

16th International Conference on Social Networks Analysis and Mining

作者： Lee, Yeonjung Cetinkaya, Yusuf Mucahit Kulah, Emre Toroslu, Hakki Davulcu, Hasan Arizona State Univ Tempe AZ 85287 USA Middle East Tech Univ Ankara Turkiye

ISBN: (纸本)9783031785375;9783031785382

Aspect-based sentiment analysis (ABSA) is a natural language processing (NLP) task, ascribing precise sentiment linkages to specific entities and issues in text data. This paper addresses critical shortcomings in current ABSA methods, particularly the issues of limited aspects, training set biases, and lack of comprehensive stance-coded datasets. First, we develop a scalable MaskedABSA approach that masks aspect terms in training sentences to enable unbiased sentiment inference from the context alone. We show that the proposed method surpasses the state-of-the-art solutions in accuracy for the aspect term sentiment classification task, as verified by the SemEval datasets. Furthermore, we tackle the perennial challenges of limited training resources and the prohibitive costs of manual annotation in ABSA dataset creation by introducing an innovative weak supervision technique capitalizing on the inherent community clustering properties found within social media datasets. We utilize community detection algorithms to partition a share network into polarized groups with homogeneous adversarial stances, allowing large-scale aspect-based sentiment analysis dataset curation without labor intensive manual labeling. Our methodology is also validated using a real-world polarized dataset comprising diverse aspects and stances to showcase its efficacy and scalability.

关键词： aspect-based sentiment analysis social networks weakly labeled data social media

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PARFAITE: PageRank-Matrix Factorization for Interpretable Graph Embeddings 16th

PARFAITE: PageRank-Matrix Factorization for Interpretable Gr...

引用

16th International Conference on Social Networks Analysis and Mining

作者： Damay, Gabriel Sozio, Mauro Telecom Paris Inst Polytech Paris Palaiseau France

ISBN: (纸本)9783031785405;9783031785412

There have been increasing efforts in recent years to develop so-called graph embeddings, which among other things allow to employ standard machine learning techniques to solve urgent real-world problems. However, developing interpretable graph embeddings has received much less attention. In our work, we develop Parfaite, an algorithm for finding an interpretable and effective graph embedding, based on the factorization of the PageRank matrix of the input graph. We evaluate the interpretability of our method against popular graph embedding techniques, such as node2vec, showing that Parfaite boasts significantly higher interpretability scores. Another contribution of our work is the release of a novel dataset constructed from all pages of the French version of Wikipedia, which we release for reproducibility and benchmarking.

关键词： network embedding interpretability personalized PageRank graph mining

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El Centro (The Downtown): A Collaborative Transmedia Project Among Ibero-American Universities 17th

El Centro (The Downtown): A Collaborative Transmedia Project...

引用

17th International Conference on Interactive Digital Storytelling

作者： Ferrer, Iliana Angel-Torres, Alejandro Univ Autonoma Barcelona Carrer La Vinya S-N Barcelona 08193 Spain Univ Bogota Jorge Tadco Lozano UTADEO Cra 4 22-61 Bogota Colombia

ISBN: (纸本)9783031784491;9783031784507

"El Centro" (The Downtown) is an inter-university collaborative transmedia project. This collective experiment of transmedia non-fiction narratives in Ibero-America seeks to innovate in the teaching of audiovisual languages and transmedia narratives in communication-related degrees, through the creation of multiformat content by undergraduate students from the Universitat Autonoma de Barcelona in Spain, Universidad Jorge Tadeo Lozano in Bogota, Universidad Panamericana in Mexico City, and Universidad Internacional de Ecuador in Quito. Using Project-Based Learning (PBL), students worked in multidisciplinary teams to produce nonfiction narratives that expand across various platforms and formats. This approach encourages the practical application of theoretical principles, the development of critical thinking, and the acquisition of skills in conventional and emerging technologies. Creative expression, teamwork, and cultural exchange were also encouraged. The content produced by the students will be disseminated in university media and other platforms (websites, social networks, events, etc.).

关键词： Transmedia IberoAmerica Teaching Innovation Project Collaborative Work Expanded Documentary Interactive Documentary University Undergraduate

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Role-Playing of Misconceptions in Teacher Training: Enhancing Pre-service Teachers' Understanding of Students' Programming Processes 17th

Role-Playing of Misconceptions in Teacher Training: Enhancin...

引用

17th International Conference on Informatics in Schools: Situation, Evolution and Perspectives-ISSEP

作者： Weinert, Martin Krone, Hendrik TU Dortmund Univ Dortmund Germany

ISBN: (纸本)9783031734731;9783031734748

To teach programming effectively, instructors must possess diagnostic skills and the ability to provide individualized interventions. This requires a deep understanding of students' mental models and common misconceptions in programming, along with the capacity to assist students in refining their mental models where necessary. In our approach, we utilize videos depicting secondary school students' programming processes to train pre-service teachers in diagnostic skills. While these videos facilitate initial diagnoses, they alone cannot confirm them. Therefore, a complementary method is essential to teach diagnostic conversations and interventions effectively. To address this need, we developed tasks that aim at these skills by incorporating role-playing of students with misconceptions. Our research focused on evaluating pre-service teachers' engagement with these tasks and their reported outcomes. Our findings reveal that it is hard for them to get into the mind of a student who holds misconceptions. They also report that trying to do so is useful for understanding students' thought processes. The results suggest that role-playing tasks can foster the transition from theoretical knowledge about mental models to the practical ability to simulate their effects. In this way, our tasks contribute to bridging the gap between theory and practice in teacher training.

关键词： Teacher Training Diagnostic Skills Mental Models Misconceptions Programming

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Overlapping Expectations: Studying the Genre Relationship of Open-World and Ecocritical Genres 17th

Overlapping Expectations: Studying the Genre Relationship of...

引用

17th International Conference on Interactive Digital Storytelling

作者： Gonzales, Ian Fisher, Joshua A. Ball State Univ Coll Commun Informat & Media Ctr Emerging Media Design & Dev Munce IN 47306 USA

ISBN: (纸本)9783031784521;9783031784538

While feature-level and media-specific frameworks are used throughout game scholarship, genre-focused analysis remains underutilized. This absence stems from a misunderstanding of genres as lists of deployed features. Rather genres shape and are shaped by audience expectations and reinforced through interactions within a discourse community. Understood in this way, genre-focused analysis is a socio-cultural-technologically mediated contextual framework that anchors context-driven analysis of interactive digital narratives and other forms of interactive storytelling. This study demonstrates genre-focused analysis by elevating feature-level analyses of Horizon Zero Dawn. While existing scholarship identifies a thematic incoherence in Horizon Zero Dawn, this study argues that these issues are a result of tension between the ecocritical and open-world genres within a particular moment in time. The work demonstrates genre-focused analysis' necessity, implementation, and value in game studies and IDN scholarship.

关键词： Genre-focused Analysis Genre Relationships Audience Expectations

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Empowering Airline Route Decisions with LLM-Generated Pseudo-labels and Zero-Shot Review Prediction 16th

Empowering Airline Route Decisions with LLM-Generated Pseudo...

引用

16th International Conference on Social Networks Analysis and Mining

作者： Alhamadani, Abdulaziz Althubiti, Khadija He, Jianfeng Sarkar, Shailik Alkulaib, Lulwah Shaik, Abdul Raheem Lee, Seungwon Khan, Mahmood Lu, Chang-Tien Florida Polytech Univ Dept Data Sci & Business Analyt Lakeland FL 33805 USA Virginia Tech Dept Hosp & Tourism Management Falls Church VA 22043 USA Virginia Tech Dept Comp Sci Falls Church VA 22043 USA Kuwait Univ Dept Comp Sci Kuwait Kuwait Virginia Tech Bradley Dept Elect & Comp Engn Falls Church VA 22043 USA George Mason Univ Tourism & Events Management Manassas VA USA

ISBN: (纸本)9783031785535;9783031785542

The airline industry has suffered a severe impact due to the COVID-19 pandemic. It resulted in significant financial losses. Strategic route planning is now an urgent need to mitigate the ongoing crisis. Motivated by the importance of customer sentiment in informing airline route decisions, this paper presents EAGLE (Enhancing Airline Groundtruth Labels and rEview rating prediction), a novel two-stage framework that leverages the power of Large Language Models (LLMs) to address the limitations of current works, which often rely on manual labeling and traditional machine learning models. In the first phase, EAGLE introduces a pseudo-labeling approach using LLMs to automatically label customer reviews to reduce the need for manual annotation and mitigate potential biases that exist in human labeling. The second phase employs a zero-shot LLM-based text classification method to predict customer sentiment and preferences from online reviews to provide a more accurate and context-aware analysis of customer feedback. Through extensive experiments, we demonstrate the effectiveness and robustness of EAGLE to demonstrate its superior performance compared to existing techniques. The proposed framework empowers airline companies to make data-driven decisions about route expansions, considering customer preferences and sentiments. Our contribution fibs in enhancing the objectivity of sentiment analysis and providing a comprehensive and scalable solution for airline route planning in the post-pandemic era, eventually leading to improved customer satisfaction and optimized operations.

关键词： Airline industry Large Language Model Text Generation Social media data mining

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VLP: A Label Propagation Algorithm for Community Detection in Complex Networks 16th

VLP: A Label Propagation Algorithm for Community Detection i...

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16th International Conference on Social Networks Analysis and Mining

作者： Boddu, Sharon Khan, Maleq Nijim, Mais Texas A&M Univ Dept Elect Engn & Comp Sci Kingsville TX 78363 USA

ISBN: (纸本)9783031785375;9783031785382

Community detection is a commonly encountered problem in social network analysis and many other areas. A community in a graph or network is a subgraph containing vertices that are closely connected to other vertices within the same subgraph but have fewer connections to the other vertices. Community detection is useful in analyzing complex systems and recognizing underlying patterns and structures that govern them. There are several algorithms that currently exist for community detection, ranging from simple and fast approaches, such as the label propagation algorithm (LPA), to more complex and time-consuming methods, such as the state-of-the-art Louvain method. We propose a new method called vector label propagation (VLP), which is a generalization of the LPA approach. The VLP algorithm significantly enhances the quality of the detected communities compared to LPA while being much faster than the Louvain method. For example, on the Twitter network, VLP has a normalized mutual information (NMI) score of 0.82, while LPA has an NMI score of 0.47. With rigorous experimentations, we demonstrate that the VLP algorithm is significantly faster than state-of-the-art algorithms such as Louvain and Infomap. On the Twitter network, VLP is 2.8 times faster than Louvain.

关键词： Community detection graph algorithms network analysis graph mining

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Proactive Refresh for Accountable Threshold Signatures 28th

Proactive Refresh for Accountable Threshold Signatures

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28th International Conference on Financial Cryptography and Data Security

作者： Boneh, Dan Partap, Aditi Rotem, Lior Stanford Univ Stanford CA 94305 USA

ISBN: (纸本)9783031786785;9783031786792

An accountable threshold signature (ATS) is a threshold signature scheme where every signature identifies the quorum of signers who generated that signature. They are widely used in financial settings where signers need to be held accountable for threshold signatures they generate. In this work we construct the first accountable threshold signature schemes that support a proactive refresh. Proactive refresh is a protocol that lets the group of signers refresh their shares of the secret key, without changing the public key or the threshold. It is an important security mechanism that helps protect a secret key from a gradual exposure of key shares. However, until now, no ATS scheme supported a proactive refresh. We begin by giving several definitions for this new concept that achieve different levels of security. We then construct three types of ATS schemes with proactive refresh. The first is a generic construction that is efficient when the number of signers is small. The second is a collection of very practical constructions derived from ATS versions of the Schnorr and BLS signature schemes;however these practical constructions only satisfy our weaker notion of security. The third is a hybrid construction that performs well for a large number of signers and satisfies our strongest security definition.

关键词： Authentication Protocol

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