Classifying the stance of individuals on controversial topics and uncovering their concerns is crucial for social scientists and policymakers. Data from Online Social Networks (OSNs), which serve as a proxy to a repre...
ISBN:
(纸本)9783031785375;9783031785382
Classifying the stance of individuals on controversial topics and uncovering their concerns is crucial for social scientists and policymakers. Data from Online Social Networks (OSNs), which serve as a proxy to a representative sample of society, offers an opportunity to classify these stances, discover society's concerns regarding controversial topics, and track the evolution of these concerns over time. Consequently, stance classification in OSNs has garnered significant attention from researchers. However, most existing methods for this task often rely on labelled data and utilise the text of users' posts or the interactions between users, necessitating large volumes of data, considerable processing time, and access to information that is not readily available (e.g. users' followers/followees). This paper proposes a lightweight approach for the stance classification of users and keywords in OSNs, aiming at understanding the collective opinion of individuals and their concerns. Our approach employs a tailored random walk model, requiring just one keyword representing each stance, using solely the keywords in social media posts. Experimental results demonstrate the superior performance of our method compared to the baselines, excelling in stance classification of users and keywords, with a running time that, while not the fastest, remains competitive.
This paper reports on a diverse corpus of 42 syllabi focused on teaching Interactive Digital Narratives (IDN) or that teach IDN applications in different fields such as education, cultural heritage, and journalism. Th...
ISBN:
(纸本)9783031784521;9783031784538
This paper reports on a diverse corpus of 42 syllabi focused on teaching Interactive Digital Narratives (IDN) or that teach IDN applications in different fields such as education, cultural heritage, and journalism. The collected syllabi represent nearly every continent and four languages, with English as the common language. The syllabi are divided into four sections: survey, humanities, design and technology, and social sciences, according to their focus. This study investigates IDN instruction's objectives, course structure, course materials, and assignments. We use comparative analysis to discover similarities and unique strengths in teaching approaches that reflect the diverse cultural and institutional contexts influencing IDN pedagogy. This early overview offers insight into the pedagogical tactics implemented in IDN studies and serves to concretize the field's approach to training practitioners and academics.
The article discusses the most important aspects of implementing the computerscience curriculum for early school education (grades 1-3) in Poland. The emphasis is on the spiral development of students' computatio...
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ISBN:
(纸本)9783031734731;9783031734748
The article discusses the most important aspects of implementing the computerscience curriculum for early school education (grades 1-3) in Poland. The emphasis is on the spiral development of students' computational thinking and knowledge and skills through the use of various physical and mental tools and environments provided by different stakeholders, as well as through the use of computers and computers in the background. The proposed approach is used in professional development courses for teachers of grades K-3 offered by several universities, and then teachers introduce this approach to their classes. The preliminary results of the effectiveness of the presented proposal are encouraging and will be published elsewhere.
The acquisition of control structures in programming poses a significant challenge for K12 students, often requiring more time than typically allocated in standard lecture schedules. This study uses three distinct exp...
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ISBN:
(纸本)9783031734731;9783031734748
The acquisition of control structures in programming poses a significant challenge for K12 students, often requiring more time than typically allocated in standard lecture schedules. This study uses three distinct experiment groups to investigate the efficacy of different instructional approaches to learning control structures. One group (our baseline) consisted of K12 students with prior programming experience. Another group included novices who received a conventional introduction to control structures. Finally, a third group, also comprised of novices, engaged in an intensive unit employing the "human robot" method, which heavily emphasized control structures. Our findings indicate that even for students with prior experience, mastery of control structures demands extended practice and instructional time. Notably, the "human robot" method significantly enhanced the understanding of control structures among novices, suggesting that more dedicated time and innovative teaching strategies are crucial for effectively teaching these fundamental concepts. Consequently, we recommend that computerscience lessons allocate additional time and employ active learning techniques to ensure students develop a robust grasp of control structures.
A considerable amount of scholarly study has been done on the art of "Stand-Up" comedy, particular American Stand-Up, on its history and vaudevillian origins, and its impact on several fields such as teachin...
ISBN:
(纸本)9783031785535;9783031785542
A considerable amount of scholarly study has been done on the art of "Stand-Up" comedy, particular American Stand-Up, on its history and vaudevillian origins, and its impact on several fields such as teaching, public communication, politics, and culture. However, there is a striking absence of studies that quantitatively examine the origins and patterns of artistic influences on the work of American Stand-Up comedians. In this paper, we attempted to fill that gap. We analyzed artistic influence, an intrinsically unmeasurable variable, using a set of observable proxies. Using these proxies, we modeled artistic influences on American Stand-Up comedians as a social influence network and studied the diffusion of influence through this network. We found that chains of artistic influence on American Stand-Up comedians originated from times much older than the vaudevillian era of the late 1800s to early 1900s. Indeed, they originated from European writers of the late middle ages. We also found that an overwhelming volume (91.23%) of direct artistic influence on American Stand-Up comedians came from individuals who were at most two generations (50 years) older than the influenced comedians, and more than half (55.73%) of the direct influence came from individuals of the same generation. We found the total volume of artistic influence (direct and indirect) on the American Stand-Up comedians followed a pronounced Pareto pattern with 11.40% and 16.67% of influencers contributing respectively 79.64% and 90.06% of the total influence volume. We also found the social influence network of American Stand-Up comedians to exhibit "small-world" network behavior.
In this article, we present a regional overview of teachers' knowledge to teach informatics. It was obtained through a self-reported quantitative evaluation instrument of informatics teachers' knowledge addres...
ISBN:
(纸本)9783031734731;9783031734748
In this article, we present a regional overview of teachers' knowledge to teach informatics. It was obtained through a self-reported quantitative evaluation instrument of informatics teachers' knowledge addressing the seven domains of the Technological Pedagogical Content Knowledge (TPACK) model. Sixty-four teachers of French-speaking Switzerland participated from various educational levels, including primary, secondary, and higher education. While primary teachers had mostly informatics education during their teacher education, upper-secondary teachers all had informatics as a major or secondary topic in the university. Using dimensionality reduction techniques (Principal Component Analysis and Factor Analysis), we extract the latent features from the knowledge expressed according to the seven domains of TPACK. Subsequently, executing an agglomerative hierarchical clustering, we group the teachers in clusters and explore the relations between those clusters and their professional profile. As a result, we can say that upper-secondary teachers express higher knowledge both on the didactical and foundational aspects of informatics teaching. Primary and lower-secondary teachers express low self-efficacy in domains related to the contents of informatics and higher self-efficacy in domains related to technology. This process facilitated the identification of adjustments that could be integrated into teacher education programs to address these needs.
Event detection from social media has been researched intensively and applied to many social problems such as disaster monitoring, rumor detection, and product sales prediction. In this paper, we deal with the underly...
ISBN:
(纸本)9783031785375;9783031785382
Event detection from social media has been researched intensively and applied to many social problems such as disaster monitoring, rumor detection, and product sales prediction. In this paper, we deal with the underlying task of event representation. Existing works use topic modeling or graph embedding to extract events from text corpora, but have not fully utilized the available information. We propose a novel model called Graph Topic Model Autoencoder (GTMA) for improving event representation quality. The model combines non-negative matrix factorization and graph autoencoder to take advantages of the document-word matrix and the word-word co-occurrence graph. The model outputs event embeddings that can be used for topic-based event detection. We test our approach with two real-world social media datasets. Compared to several embedding learning baselines, our model generally achieves better topic quality in event detection evaluation.
From the archive to the screen, Black digital humanists regularly engage interactive digital media as a tool of social justice-based creative placemaking. In this short paper, Alexander examines interactive digital na...
ISBN:
(纸本)9783031784491;9783031784507
From the archive to the screen, Black digital humanists regularly engage interactive digital media as a tool of social justice-based creative placemaking. In this short paper, Alexander examines interactive digital narrative as a radical worldbuilding platform, particularly for marginalized communities, and outlines a theoretical framework for Black futurist worldbuilding. This framework culminates in WILDWOOD, an afro-solarpunk interactive digital narrative that visions a rewilded future for one Southside Chicago neighborhood. WILDWOOD incorporates elements of tabletop roleplay game storytelling and interactive digital narrative methods, using hypertext fiction and chance as digital worldbuilding tools. The game explores community histories and futures through Black speculative placemaking, offering tools to imagine new visions of Black worlds and space to enact through immersive digital narrative play.
Graphs play a vital role in various applications. Graph Neural Networks (GNNs) excel at capturing topology information by using a message-passing mechanism to enrich node representations with local neighborhood inform...
ISBN:
(纸本)9783031785405;9783031785412
Graphs play a vital role in various applications. Graph Neural Networks (GNNs) excel at capturing topology information by using a message-passing mechanism to enrich node representations with local neighborhood information. Despite their success in modeling single-layer graphs, real-world scenarios often involve multi-layer graphs where nodes can have multiple edges or relationships represented as different layers. Existing methods of multi-layer graph learning struggle to efficiently process inter-layer information, as they mainly focus on preserving similar layers or shared invariant information, which may not be suitable for all situations. We propose a novel framework called Adaptive Multi-layer Graph Neural Networks (AmGNN) to address this challenge. AmGNN learns shared invariant information for nodes that need it and selectively preserves relevant layers' information for nodes not requiring shared invariance. We introduce multi-layer graph contrastive learning to efficiently capture invariant information and learn weights for adaptive processing. Our experiments on real-world multi-layer graphs validate the effectiveness of AmGNN in node classification tasks.
Lazy blockchains decouple consensus from transaction verification and execution to increase throughput. Although they can contain invalid transactions (e.g., double spends) as a result, these can easily be filtered ou...
ISBN:
(纸本)9783031786785;9783031786792
Lazy blockchains decouple consensus from transaction verification and execution to increase throughput. Although they can contain invalid transactions (e.g., double spends) as a result, these can easily be filtered out by full nodes that check if there have been previous conflicting transactions. However, creating light (SPV) clients that do not see the whole transaction history becomes a challenge: A record of a transaction on the chain does not necessarily entail transaction confirmation. In this paper, we devise a protocol that enables the creation of efficient light clients for lazy blockchains. The number of interaction rounds and the communication complexity of our protocol are logarithmic in the blockchain execution time. Our construction is based on a bisection game that traverses the Merkle tree containing the ledger of all - valid or invalid - transactions. We prove that our proof system is succinct, complete and sound, and empirically demonstrate the feasibility of our scheme.
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